Brain lipidomics as a rising field in neurodegenerative contexts: Perspectives with Machine Learning approaches

Investigation of the structural changes in the hippocampus and prefrontal cortex using FTIR spectroscopy in sleep deprived mice

Sleep is a basic, physiological requirement for living things to survive and is a process that covers one third of our lives. Melatonin is a hormone that plays an important role in the regulation of sleep. Sleep deprivation affect brain structures and functions. Sleep deprivation causes a decrease in brain activity, with particularly negative effects on the hippocampus and prefrontal cortex. Despite the essential role of protein and lipids vibrations, polysaccharides, fatty acid side chains functional groups, and ratios between amides in brain structures and functions, the brain chemical profile exposed to gentle handling sleep deprivation model versus Melatonin exposure remains unexplored. Therefore, the present study, aims to investigate a molecular profile of these regions using FTIR spectroscopy measurement's analysis based on lipidomic approach with chemometrics and multivariate analysis to evaluate changes in lipid composition in the hippocampus, prefrontal regions of the brain. In this study, C57BL/6J mice were randomly assigned to either the control or sleep deprivation group, resulting in four experimental groups: Control (C) (n = 6), Control + Melatonin (C + M) (n = 6), Sleep Deprivation (S) (n = 6), and Sleep Deprivation + Melatonin (S + M) (n = 6). Interventions were administered each morning via intraperitoneal injections of melatonin (10 mg/kg) or vehicle solution (%1 ethanol + saline), while the S and S + M groups underwent 6 h of daily sleep deprivation from using the Gentle Handling method. All mice were individually housed in cages with ad libitum access to food and water within a 12-hour light-dark cycle. Results presented that the brain regions affected by insomnia. The structure of phospholipids, changed. Yet, not only changes in lipids but also in amides were noticed in hippocampus and prefrontal cortex tissues. Additionally, FTIR results showed that melatonin affected the lipids as well as the amides fraction in cortex and hippocampus collected from both control and sleep deprivation groups.

Plasma lipidome, circulating inflammatory proteins, and Parkinson's disease: a Mendelian randomization study

Background

Observational studies have suggested that plasma lipidome play a pivotal role in the occurrence of Parkinson's disease (PD). However, it remains unknown which lipids among plasma lipidome affect PD and how they exert their influence. Clarity is lacking regarding the causal relationship between plasma lipidome and PD, as well as whether circulating inflammatory proteins serve as mediators.

Methods

Single nucleotide polymorphisms (SNPs) significantly associated with 179 plasma lipidome were selected as instrumental variables to assess their causal impact on PD. PD data, serving as the outcome, were sourced from the International Parkinson's Disease Genomics Consortium, which boasts the largest sample size to date. The inverse variance weighted (IVW), Weighted median method, MR-Egger method, Simple mode method, Weighted mode method and MR-PRESSO were employed to evaluate the influence of the 179 plasma lipidome on PD. Heterogeneity, pleiotropy tests, and reverse causality analyses were conducted accordingly. Additionally, we analyzed the causal relationship between 91 circulating inflammatory proteins and PD, exploring whether these proteins serve as mediators in the pathway from plasma lipidome to PD.

Results

Among the 179 plasma lipidome, three were found to be associated with a reduced risk of PD: Phosphatidylcholine (14:0_18:2) (IVW, OR = 0.877; 95%CI, 0.787-0.978; p = 0.018), Phosphatidylcholine (16:0_16:1) levels (IVW, OR = 0.835; 95%CI, 0.717-0.973; p = 0.021), and Phosphatidylcholine (O-17:0_17:1) levels (IVW, OR = 0.854; 95%CI, 0.779-0.936; p = 0.001). Meanwhile, Sphingomyelin (d38:1) was linked to an increased risk of PD (IVW, OR = 1.095; 95%CI, 1.027-1.166; p = 0.005). Among the 91 circulating inflammatory proteins, three were associated with a lower PD risk: Fibroblast growth factor 21 levels (IVW, OR = 0.817; 95%CI, 0.674-0.990; p = 0.039), Transforming growth factor-alpha levels (IVW, OR = 0.825; 95%CI, 0.683-0.998; p = 0.048), and Tumor necrosis factor receptor superfamily member 9 levels (IVW, OR = 0.846; 95%CI, 0.744-0.963; p = 0.011). Two were associated with a higher risk of PD: Interleukin-17A levels (IVW, OR = 1.285; 95%CI, 1.051-1.571; p = 0.014) and TNF-beta levels (IVW, OR = 1.088; 95%CI, 1.010-1.171; p = 0.026). Additionally, a positive correlation was observed between Phosphatidylcholine (14:0_18:2) levels and Fibroblast growth factor 21 levels (IVW, OR = 1.125; 95%CI, 1.006-1.257; p = 0.038), suggesting that Fibroblast growth factor 21 levels may serve as a mediating factor in the pathway between Phosphatidylcholine (14.0_18.2) levels and PD. The mediation effect was estimated to be -0.024, accounting for approximately 18% of the total effect.

Conclusion

Both plasma lipidome and circulating inflammatory proteins demonstrate a causal relationship with PD. Additionally, circulating inflammatory proteins may serve as mediators in the pathway from plasma lipidome to PD. These findings may contribute to the prediction and diagnosis of PD and potentially pave the way for targeted therapies in the future.

Diet Supplemented with Special Formula Milk Powder Promotes the Growth of the Brain in Rats

This investigation was to study the effects of different formula components on the brain growth of rats. Fifty male SD rats were randomly divided into five groups: a basic diet group; a 20% ordinary milk powder group; a 20% special milk powder group; a 30% ordinary milk powder group; and a 30% special milk powder group by weight. LC-MS was used to detect brain lipidomics. After 28 days of feeding, compared with the basic diet group, the brain/body weights of rats in the 30% ordinary milk powder group were increased. The serum levels of 5-HIAA in the 30% ordinary milk powder group were lower than in the 20% ordinary milk powder group. Compared with the basic diet group, the expressions of DLCL, MePC, PI, and GM1 were higher in the groups with added special milk powder, while the expressions of LPE, LdMePE, SM, and MGTG were higher in the groups with added ordinary milk powder. The expression of MBP was significantly higher in the 20% ordinary group. This study found that different formula components of infant milk powder could affect brain growth in SD rats. The addition of special formula infant milk powder may have beneficial effects on rat brains by regulating brain lipid expression.

The marine-derived compound TAG alleviates Parkinson's disease by restoring RUBCN-mediated lipid metabolism homeostasis

Parkinson's disease (PD) is the second most common neurodegenerative disease, and its prevalence is increasing. Currently, no effective therapies for PD exist. Marine-derived natural compounds are considered important resources for the discovery of new drugs due to their distinctive structures and diverse activities. In this study, tetrahydroauroglaucin (TAG), a polyketide isolated from a marine sponge, was found to have notable neuroprotective effects on MPTP/MPP+-induced neurotoxicity. RNA sequencing analysis and metabolomics revealed that TAG significantly improved lipid metabolism disorder in PD models. Further investigation indicated that TAG markedly decreased the accumulation of lipid droplets (LDs), downregulated the expression of RUBCN, and promoted autophagic flux. Moreover, conditional knockdown of Rubcn notably attenuated PD-like symptoms and the accumulation of LDs, accompanied by blockade of the neuroprotective effect of TAG. Collectively, our results first indicated that TAG, a promising PD therapeutic candidate, could suppress the accumulation of LDs through the RUBCN-autophagy pathway, which highlighted a novel and effective strategy for PD treatment.

Phospholipidomics in Clinical Trials for Brain Disorders: Advancing our Understanding and Therapeutic Potentials

Phospholipidomics is a specialized branch of lipidomics that focuses on the characterization and quantification of phospholipids. By using sensitive analytical techniques, phospholipidomics enables researchers to better understand the metabolism and activities of phospholipids in brain disorders such as Alzheimer's and Parkinson's diseases. In the brain, identifying specific phospholipid biomarkers can offer valuable insights into the underlying molecular features and biochemistry of these diseases through a variety of sensitive analytical techniques. Phospholipidomics has emerged as a promising tool in clinical studies, with immense potential to advance our knowledge of neurological diseases and enhance diagnosis and treatment options for patients. In the present review paper, we discussed numerous applications of phospholipidomics tools in clinical studies, with a particular focus on the neurological field. By exploring phospholipids' functions in neurological diseases and the potential of phospholipidomics in clinical research, we provided valuable insights that could aid researchers and clinicians in harnessing the full prospective of this innovative practice and improve patient outcomes by providing more potent treatments for neurological diseases.

Artificial intelligence-driven drug repositioning uncovers efavirenz as a modulator of α-synuclein propagation: Implications in Parkinson's disease

Parkinson's disease (PD) is a complex neurodegenerative disorder with an unclear etiology. Despite significant research efforts, developing disease-modifying treatments for PD remains a major unmet medical need. Notably, drug repositioning is becoming an increasingly attractive direction in drug discovery, and computational approaches offer a relatively quick and resource-saving method for identifying testable hypotheses that promote drug repositioning. We used an artificial intelligence (AI)-based drug repositioning strategy to screen an extensive compound library and identify potential therapeutic agents for PD. Our AI-driven analysis revealed that efavirenz and nevirapine, approved for treating human immunodeficiency virus infection, had distinct profiles, suggesting their potential effects on PD pathophysiology. Among these, efavirenz attenuated α-synuclein (α-syn) propagation and associated neuroinflammation in the brain of preformed α-syn fibrils-injected A53T α-syn Tg mice and α-syn propagation and associated behavioral changes in the C. elegans BiFC model. Through in-depth molecular investigations, we found that efavirenz can modulate cholesterol metabolism and mitigate α-syn propagation, a key pathological feature implicated in PD progression by regulating CYP46A1. This study opens new avenues for further investigation into the mechanisms underlying PD pathology and the exploration of additional drug candidates using advanced computational methodologies.

Spatial Heterogeneity of Brain Lipids in SIV-Infected Macaques Treated with Antiretroviral Therapy

Human immunodeficiency virus (HIV) infection continues to promote neurocognitive impairment, mood disorders, and brain atrophy, even in the modern era of viral suppression. Brain lipids are vulnerable to HIV-associated energetic strain and may contribute to HIV-associated neurologic dysfunction due to alterations in lipid breakdown and structural lipid composition. HIV neuropathology is region dependent, yet there has not been comprehensive characterization of the spatial heterogeneity of brain lipids during infection that possibly impacts neurologic function. To address this gap, we evaluated the spatial lipid distribution using matrix laser desorption/ionization imaging mass spectrometry (MALDI-IMS) across four brain regions (parietal cortex, midbrain, thalamus, and temporal cortex), as well as the kidney for a peripheral tissue control, in a simian immunodeficiency virus (SIV)-infected rhesus macaque treated with a course of antiretroviral therapies (ARTs). We assessed lipids indicative of fat breakdown [acylcarnitines (CARs)] and critical structural lipids [phosphatidylcholines (PCs) and phosphatidylethanolamines (PEs)] across fatty acid chain lengths and degrees of unsaturation. CARs with very long-chain, polyunsaturated fatty acids (PUFAs) were more abundant across all brain regions than shorter chain, saturated, or monounsaturated species. We observed distinct brain lipid distribution patterns for the CARs and PCs. However, no clear expression patterns emerged for PEs. Surprisingly, the kidney was nearly devoid of ions corresponding to PUFAs common in brain. PEs and PCs with PUFAs had little intensity and less density than other species, and only one CAR species was observed in kidney at high intensity. Overall, our study demonstrates the stark variation in structural phospholipids and lipid-energetic intermediates present in the virally suppressed SIV-macaque brain. These findings may be useful for identifying regional vulnerabilities to damage due to brain lipid changes in people with HIV.

Cerebrospinal fluid neutral lipids predict progression from mild cognitive impairment to Alzheimer's disease

Genetic, metabolic, and clinical evidence links lipid dysregulation to an increased risk of Alzheimer's disease (AD). However, the role of lipids in the pathophysiological processes of AD and its clinical progression is unclear. We investigated the association between cerebrospinal fluid (CSF) lipidome and the pathological hallmarks of AD, progression from mild cognitive impairment (MCI) to AD, and the rate of cognitive decline in MCI patients. The CSF lipidome was analyzed by liquid chromatography coupled to mass spectrometry in an LC-ESI-QTOF-MS/MS platform for 209 participants: 91 AD, 92 MCI, and 26 control participants. The MCI patients were followed up for a median of 58 (± 12.5) months to evaluate their clinical progression to AD. Forty-eight (52.2%) MCI patients progressed to AD during follow-up. We found that higher CSF levels of hexacosanoic acid and ceramide Cer(d38:4) were associated with an increased risk of amyloid beta 42 (Aβ42) positivity in CSF, while levels of phosphatidylethanolamine PE(40:0) were associated with a reduced risk. Higher CSF levels of sphingomyelin SM(30:1) were positively associated with pathological levels of phosphorylated tau in CSF. Cholesteryl ester CE(11D3:1) and an unknown lipid were recognized as the most associated lipid species with MCI to AD progression. Furthermore, TG(O-52:2) was identified as the lipid most strongly associated with the rate of progression. Our results indicate the involvement of membrane and intracellular neutral lipids in the pathophysiological processes of AD and the progression from MCI to AD dementia. Therefore, CSF neutral lipids can be used as potential prognostic markers for AD.

Optimized Lipidomics Extraction of Sphingosine and Sphinganine from Optic Nerve for Signaling Studies

Interconvertible sphingolipid metabolites represent germane constituents of eukaryotic membranes and are vital in the regulation of cellular homeostasis, proliferation, survival, and induction of autophagy. This protocol describes a step-by-step method for extractions of sphingosine and sphinganine from mammalian tissue samples, particularly from the murine optic nerve. These lipids are partitioned into a binary mixture of chloroform and methanol in a modified Bligh and Dyer method. This is followed with reverse phase ultrahigh-performance liquid chromatography fractionation with a C18+ column and subsequent tandem mass spectrometry (UHPLC-MS-MS) analysis of the biological abundance. These free sphingoid bases dissociate to form structurally distinctive carbocation product ions that can be confirmed with annotations of lipidomic databases or in-house fragmentation software.

Machine learning in Alzheimer's disease drug discovery and target identification

Alzheimer's disease (AD) stands as a formidable neurodegenerative ailment that poses a substantial threat to the elderly population, with no known curative or disease-slowing drugs in existence. Among the vital and time-consuming stages in the drug discovery process, disease modeling and target identification hold particular significance. Disease modeling allows for a deeper comprehension of disease progression mechanisms and potential therapeutic avenues. On the other hand, target identification serves as the foundational step in drug development, exerting a profound influence on all subsequent phases and ultimately determining the success rate of drug development endeavors. Machine learning (ML) techniques have ushered in transformative breakthroughs in the realm of target discovery. Leveraging the strengths of large dataset analysis, multifaceted data processing, and the exploration of intricate biological mechanisms, ML has become instrumental in the quest for effective AD treatments. In this comprehensive review, we offer an account of how ML methodologies are being deployed in the pursuit of drug discovery for AD. Furthermore, we provide an overview of the utilization of ML in uncovering potential intervention strategies and prospective therapeutic targets for AD. Finally, we discuss the principal challenges and limitations currently faced by these approaches. We also explore the avenues for future research that hold promise in addressing these challenges.

Oxidative damage in neurodegeneration: roles in the pathogenesis and progression of Alzheimer disease

Alzheimer disease (AD) is associated with multiple etiologies and pathological mechanisms, among which oxidative stress (OS) appears as a major determinant. Intriguingly, OS arises in various pathways regulating brain functions, and it seems to link different hypotheses and mechanisms of AD neuropathology with high fidelity. The brain is particularly vulnerable to oxidative damage, mainly because of its unique lipid composition, resulting in an amplified cascade of redox reactions that target several cellular components/functions ultimately leading to neurodegeneration. The present review highlights the "OS hypothesis of AD," including amyloid beta-peptide-associated mechanisms, the role of lipid and protein oxidation unraveled by redox proteomics, and the antioxidant strategies that have been investigated to modulate the progression of AD. Collected studies from our groups and others have contributed to unraveling the close relationships between perturbation of redox homeostasis in the brain and AD neuropathology by elucidating redox-regulated events potentially involved in both the pathogenesis and progression of AD. However, the complexity of AD pathological mechanisms requires an in-depth understanding of several major intracellular pathways affecting redox homeostasis and relevant for brain functions. This understanding is crucial to developing pharmacological strategies targeting OS-mediated toxicity that may potentially contribute to slow AD progression as well as improve the quality of life of persons with this severe dementing disorder.

Lipidomic profiling study on neurobehavior toxicity in zebrafish treated with aflatoxin B1

Mycotoxin aflatoxin B1 (AFB1) has been proven to cause neurotoxicity, but its potential interference with the normal function of brain tissue is not fully defined. As the indispensable role of lipids in maintaining the normal function of brain tissue, the aim of this study is to clarify the effect of AFB1 short-term (7 days) exposure on brain tissue from the perspective of lipid metabolism. In this study, zebrafish were exposed to two concentrations (5, 20 μg/L). Through quantitative analysis of AFB1, the detection of AFB1 in zebrafish brain tissue was discovered for the first time, combined with the changes in zebrafish neurobehavior, the occurrence of brain injury was deduced. Subsequently, 1734 lipids in zebrafish brain tissue were mapped using ion mobility time-of-flight mass spectrometry (UPLC-QTOF-IMS-MS), which has great advantages in lipid detection. Comparative analysis of the abnormal lipid metabolism in zebrafish brain revealed 114 significantly changed lipids, mainly involving two pathways of sphingolipid metabolism and fatty acid degradation. This study discovered the detection of AFB1 in the brain and revealed a potential link between AFB1-induced behavioral abnormalities and lipid metabolism disorders in brain tissue, providing reliable evidence for elucidating the neurotoxicity of AFB1.

Alterations of Oligodendrocyte and Myelin Energy Metabolism in Multiple Sclerosis

Multiple sclerosis (MS) is a complex autoimmune disease of the central nervous system (CNS), characterized by demyelination and neurodegeneration. Oligodendrocytes play a vital role in maintaining the integrity of myelin, the protective sheath around nerve fibres essential for efficient signal transmission. However, in MS, oligodendrocytes become dysfunctional, leading to myelin damage and axonal degeneration. Emerging evidence suggests that metabolic changes, including mitochondrial dysfunction and alterations in glucose and lipid metabolism, contribute significantly to the pathogenesis of MS. Mitochondrial dysfunction is observed in both immune cells and oligodendrocytes within the CNS of MS patients. Impaired mitochondrial function leads to energy deficits, affecting crucial processes such as impulse transmission and axonal transport, ultimately contributing to neurodegeneration. Moreover, mitochondrial dysfunction is linked to the generation of reactive oxygen species (ROS), exacerbating myelin damage and inflammation. Altered glucose metabolism affects the energy supply required for oligodendrocyte function and myelin synthesis. Dysregulated lipid metabolism results in changes to the composition of myelin, affecting its stability and integrity. Importantly, low levels of polyunsaturated fatty acids in MS are associated with upregulated lipid metabolism and enhanced glucose catabolism. Understanding the intricate relationship between these mechanisms is crucial for developing targeted therapies to preserve myelin and promote neurological recovery in individuals with MS. Addressing these metabolic aspects may offer new insights into potential therapeutic strategies to halt disease progression and improve the quality of life for MS patients.

Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information, with its application to neuroscience termed neuroinformatics. Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms, which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases. Importantly, integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile. In this review, we first summarize data mining studies utilizing datasets from the individual type of omics analysis, including epigenetics/epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and spatial omics, pertaining to Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We then discuss multi-omics integration approaches, including independent biological integration and unsupervised integration methods, for more intuitive and informative interpretation of the biological data obtained across different omics layers. We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks. Finally, we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery, therapeutic development, and elucidation of disease mechanisms. We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

First insights into region-specific lipidome alterations of prefrontal cortex and hippocampus of mice exposed chronically to microcystins

Microcystins (MCs), a group of most widespread freshwater cyanotoxins that possess strong neurotoxicity, can adversely affect brain structures and functions and are linked to neurodegenerative diseases. Despite the essential role of lipids in brain structures and functions, the brain lipidome profile of mammals exposed to MCs remains unexplored, hindering a clear understanding of the neurotoxic effects of MCs and underlying mechanisms. In this study, we performed untargeted lipidomic profiling using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) on the prefrontal cortex and hippocampus of mice orally exposed to 30 and 300 μg/kg body mass/day of microcystin-leucine arginine (MC-LR) for 180 days to evaluate the impacts of MC-LR on the brain lipidome profile and functions. Our results show that MC-LR resulted in a decline in cognitive parameters, as assessed by the Morris water maze test. Interestingly, apparent neurodegenerative changes were observed in the prefrontal cortex, but not in the hippocampus. Comprehensive lipidomic analyses uncovered profound, region-specific changes in the phospholipid and sphingolipid profile at the levels of lipid subclasses, lipid species, and fatty acyl composition. These changes showed overall decrease trends of lipid content in the prefrontal cortex yet increasing trends in the hippocampus. We identified distinct transcriptional regulations of lipid metabolism and apoptosis by MC-LR in the two regions, which appeared to underlie the neurodegenerative changes. Collectively, this study uncovers region-specific changes in the brain lipidome profile and functions induced by MCs, shedding light on the role of lipid dysfunction in neurotoxicity mechanism of MCs.

Erythrocyte Plasma Membrane Lipid Composition Mirrors That of Neurons and Glial Cells in Murine Experimental In Vitro and In Vivo Inflammation

Lipid membrane turnover and myelin repair play a central role in diseases and lesions of the central nervous system (CNS). The aim of the present study was to analyze lipid composition changes due to inflammatory conditions. We measured the fatty acid (FA) composition in erythrocytes (RBCs) and spinal cord tissue (gas chromatography) derived from mice affected by experimental allergic encephalomyelitis (EAE) in acute and remission phases; cholesterol membrane content (Filipin) and GM1 membrane assembly (CT-B) in EAE mouse RBCs, and in cultured neurons, oligodendroglial cells and macrophages exposed to inflammatory challenges. During the EAE acute phase, the RBC membrane showed a reduction in polyunsaturated FAs (PUFAs) and an increase in saturated FAs (SFAs) and the omega-6/omega-3 ratios, followed by a restoration to control levels in the remission phase in parallel with an increase in monounsaturated fatty acid residues. A decrease in PUFAs was also shown in the spinal cord. CT-B staining decreased and Filipin staining increased in RBCs during acute EAE, as well as in cultured macrophages, neurons and oligodendrocyte precursor cells exposed to inflammatory challenges. This regulation in lipid content suggests an increased cell membrane rigidity during the inflammatory phase of EAE and supports the investigation of peripheral cell membrane lipids as possible biomarkers for CNS lipid membrane concentration and assembly.

Brain N-Glycosylation and Lipidomic Profile Changes Induced by a High-Fat Diet in Dyslipidemic Hamsters

The consumption of diets rich in saturated fats is known to be associated with higher mortality. The adoption of healthy habits, for instance adhering to a Mediterranean diet, has proved to exert a preventive effect towards cardiovascular diseases and dyslipidemia. Little is known about how a suboptimal diet can affect brain function, structure, and the mechanisms involved. The aims of this study were to examine how a high-fat diet can alter the brain N-glycan and lipid profile in male Golden Syrian hamsters and to evaluate the potential of a Mediterranean-like diet to reverse this situation. During twelve weeks, hamsters were fed a normal fat diet (CTRL group), a high-fat diet (HFD group), and a high-fat diet followed by a Mediterranean-like diet (MED group). Out of seventy-two identified N-glycans, fourteen were significant (p < 0.05) between HFD and CTRL groups, nine between MED and CTRL groups, and one between MED and HFD groups. Moreover, forty-nine lipids were altered between HFD and CTRL groups, seven between MED and CTRL groups, and five between MED and HFD groups. Our results suggest that brain N-glycan composition in high-fat diet-fed hamsters can produce events comparable to those found in some neurodegenerative diseases, and may promote brain ageing.

AntDAS-DDA: A New Platform for Data-Dependent Acquisition Mode-Based Untargeted Metabolomic Profiling Analysis with Advantage of Recognizing Insource Fragment Ions to Improve Compound Identification

Data-dependent acquisition (DDA) mode in ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) can provide massive amounts of MS¹ and MS/MS information of compounds in untargeted metabolomics and can thus facilitate compound identification greatly. In this work, we developed a new platform called AntDAS-DDA for the automatic processing of UHPLC-HRMS data sets acquired under the DDA mode. Several algorithms, including extracted ion chromatogram extraction, feature extraction, MS/MS spectrum construction, fragment ion identification, and MS¹ spectrum construction, were developed within the platform. The performance of AntDAS-DDA was investigated comprehensively with a mixture of standard and complex plant data sets. Results suggested that features in complex sample matrices can be extracted effectively, and the constructed MS¹ and MS/MS spectra can benefit in compound identification greatly. The efficiency of compound identification can be improved by about 20%. AntDAS-DDA can take full advantage of MS/MS information in multiple sample analyses and provide more MS/MS spectra than single sample analysis. A comparison with advanced data analysis tools indicated that AntDAS-DDA may be used as an alternative for routine UHPLC-HRMS-based untargeted metabolomics. AntDAS-DDA is freely available at http://www.pmdb.org.cn/antdasdda.

Deciphering lipid dysregulation in ALS: from mechanisms to translational medicine

Lipids, defined by low solubility in water and high solubility in nonpolar solvents, can be classified into fatty acids, glycerolipids, glycerophospholipids, sphingolipids, and sterols. Lipids not only regulate integrity and fluidity of biological membranes, but also serve as energy storage and bioactive molecules for signaling. Causal mutations in SPTLC1 (serine palmitoyltransferase long chain subunit 1) gene within the lipogenic pathway have been identified in amyotrophic lateral sclerosis (ALS), a paralytic and fatal motor neuron disease. Furthermore, lipid dysmetabolism within the central nervous system and circulation is associated with ALS. Here, we aim to delineate the diverse roles of different lipid classes and understand how lipid dysmetabolism may contribute to ALS pathogenesis. Among the different lipids, accumulation of ceramides, arachidonic acid, and lysophosphatidylcholine is commonly emerging  as detrimental to motor neurons. We end with exploring the potential ALS therapeutics by reducing these toxic lipids.

Brain lipidomics: From functional landscape to clinical significance

Lipids are crucial components of cellular function owing to their role in membrane formation, intercellular signaling, energy storage, and homeostasis maintenance. In the brain, lipid dysregulations have been associated with the etiology and progression of neurodegeneration and other neurological pathologies. Hence, brain lipids are emerging as important potential targets for the early diagnosis and prognosis of neurological diseases. This review aims to highlight the significance and usefulness of lipidomics in diagnosing and treating brain diseases. We explored lipid alterations associated with brain diseases, paying attention to organ-specific characteristics and the functions of brain lipids. As the recent advances in brain lipidomics would have been impossible without advances in analytical techniques, we provide up-to-date information on mass spectrometric approaches and integrative analysis with other omic approaches. Last, we present the potential applications of lipidomics combined with artificial intelligence techniques and interdisciplinary collaborative research for treating brain diseases with clinical heterogeneities.

Effects of Aging and Disease Conditions in Brain of Tumor-Bearing Mice: Evaluation of Purine DNA Damages and Fatty Acid Pool Changes

The consequences of aging and disease conditions in tissues involve reactive oxygen species (ROS) and related molecular alterations of different cellular compartments. We compared a murine model of immunodeficient (SCID) xenografted young (4 weeks old) and old (17 weeks old) mice with corresponding controls without tumor implantation and carried out a compositional evaluation of brain tissue for changes in parallel DNA and lipids compartments. DNA damage was measured by four purine 5',8-cyclo-2'-deoxynucleosides, 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxo-dG), and 8-oxo-7,8-dihydro-2'-deoxyadenosine (8-oxo-dA). In brain lipids, the twelve most representative fatty acid levels, which were mostly obtained from the transformation of glycerophospholipids, were followed up during the aging and disease progressions. The progressive DNA damage due to age and tumoral conditions was confirmed by raised levels of 5'S-cdG and 5'S-cdA. In the brain, the remodeling involved a diminution of palmitic acid accompanied by an increase in arachidonic acid, along both age and tumor progressions, causing increases in the unsaturation index, the peroxidation index, and total TFA as indicators of increased oxidative and free radical reactivity. Our results contribute to the ongoing debate on the central role of DNA and genome instability in the aging process, and on the need for a holistic vision, which implies choosing the best biomarkers for such monitoring. Furthermore, our data highlight brain tissue for its lipid remodeling response and inflammatory signaling, which seem to prevail over the effects of DNA damage.

Filling the Gap with Long n-Alkanes: Incorporation of C20 and C30 into Phospholipid Membranes

Investigating how hydrophobic molecules mix with phospholipid bilayers and how they affect membrane properties is commonplace in biophysics. Despite this, a molecular-level empirical description of a membrane model as simple as a phospholipid bilayer with long linear hydrophobic chains incorporated is still missing. Here, we present an unprecedented molecular characterization of the incorporation of two long n-alkanes, n-eicosane (C20) and n-triacontane (C30) with 20 and 30 carbons, respectively, in phosphatidylcholine (PC) bilayers using a combination of experimental techniques (²H NMR, ³¹P NMR, ¹H-¹³C dipolar recoupling solid-state NMR, X-ray scattering, and cryogenic electron microscopy) and atomistic molecular dynamics (MD) simulations. At low hydration, deuterated C20 and C30 yield ²H NMR spectra evidencing anisotropic-motion, which demonstrates their miscibility in PC membranes up to a critical alkane-to-acyl-chain volume fraction, ϕ_c. The acquired ²H NMR spectra of C20 and C30 have notably different lineshapes. At low alkane volume fractions below ϕ_c, CHARMM36 MD simulations predict such ²H NMR spectra qualitatively and thus enable an atomistic-level interpretation of the spectra. Above ϕ_c, the ²H NMR lineshapes become characteristic of motions in the intermediate-regime that, together with the MD simulation results, suggest the onset of immiscibility between the alkane molecules and the acyl chains. For all the systems investigated, the phospholipid molecular structure is unperturbed by the presence of the alkanes. However, at conditions of excess hydration and at surprisingly low alkane fractions below ϕ_c, a peak characteristic of isotropic motion is observed in both the ²H spectra of the alkanes and ³¹P spectra of the phospholipids, strongly indicating that the incorporation of the alkanes induces a reduction on the average radius of the lipid vesicles.

Prioritize biologically relevant ions for data-independent acquisition (BRI-DIA) in LC-MS/MS-based lipidomics analysis

INTRODUCTION

Data-dependent acquisition (DDA) is the most commonly used MS/MS scan method for lipidomics analysis on orbitrap-based instrument. However, MS instrument associated software decide the top N precursors for fragmentation, resulting in stochasticity of precursor selection and compromised consistency and reproducibility. We introduce a novel workflow using biologically relevant lipids to construct inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow.

OBJECTIVES

To ensure consistent coverage of biologically relevant lipids in LC-MS/MS-based lipidomics analysis.

METHODS

Biologically relevant ion list was constructed based on LIPID MAPS and lipidome atlas in MS-DIAL 4. Lipids were extracted from mouse tissues and used to assess different MS/MS scan workflow (DDA, BRI-DIA, and hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer.

RESULTS

DDA resulted in more MS/MS events, but the total number of unique lipids identified by three methods (DDA, BRI-DIA, and hybrid MS/MS scan mode) is comparable (580 unique lipids across 44 lipid subclasses in mouse liver). Major cardiolipin molecular species were identified by data generated using BRI-DIA and hybrid methods and allowed calculation of cardiolipin compositions, while identification of the most abundant cardiolipin CL72:8 was missing in data generated using DDA method, leading to wrong calculation of cardiolipin composition.

CONCLUSION

The method of using inclusion list comprised of biologically relevant lipids in DIA MS/MS scan is as efficient as traditional DDA method in profiling lipids, but offers better consistency of lipid identification, compared to DDA method. This study was performed using Orbitrap Exploris 480, and we will further evaluate this workflow on other platforms, and if verified by future work, this biologically relevant ion fragmentation workflow could be routinely used in many studies to improve MS/MS identification capacities.

Metabolomic Analysis of Human Astrocytes in Lipotoxic Condition: Potential Biomarker Identification by Machine Learning Modeling

The association between neurodegenerative diseases (NDs) and obesity has been well studied in recent years. Obesity is a syndrome of multifactorial etiology characterized by an excessive accumulation and release of fatty acids (FA) in adipose and non-adipose tissue. An excess of FA generates a metabolic condition known as lipotoxicity, which triggers pathological cellular and molecular responses, causing dysregulation of homeostasis and a decrease in cell viability. This condition is a hallmark of NDs, and astrocytes are particularly sensitive to it, given their crucial role in energy production and oxidative stress management in the brain. However, analyzing cellular mechanisms associated with these conditions represents a challenge. In this regard, metabolomics is an approach that allows biochemical analysis from the comprehensive perspective of cell physiology. This technique allows cellular metabolic profiles to be determined in different biological contexts, such as those of NDs and specific metabolic insults, including lipotoxicity. Since data provided by metabolomics can be complex and difficult to interpret, alternative data analysis techniques such as machine learning (ML) have grown exponentially in areas related to omics data. Here, we developed an ML model yielding a 93% area under the receiving operating characteristic (ROC) curve, with sensibility and specificity values of 80% and 93%, respectively. This study aimed to analyze the metabolomic profiles of human astrocytes under lipotoxic conditions to provide powerful insights, such as potential biomarkers for scenarios of lipotoxicity induced by palmitic acid (PA). In this work, we propose that dysregulation in seleno-amino acid metabolism, urea cycle, and glutamate metabolism pathways are major triggers in astrocyte lipotoxic scenarios, while increased metabolites such as alanine, adenosine, and glutamate are suggested as potential biomarkers, which, to our knowledge, have not been identified in human astrocytes and are proposed as candidates for further research and validation.

Integrated Metabolomics and Lipidomics Reveal High Accumulation of Glycerophospholipids in Human Astrocytes under the Lipotoxic Effect of Palmitic Acid and Tibolone Protection

Lipotoxicity is a metabolic condition resulting from the accumulation of free fatty acids in non-adipose tissues which involves a series of pathological responses triggered after chronic exposure to high levels of fatty acids, severely detrimental to cellular homeostasis and viability. In brain, lipotoxicity affects both neurons and other cell types, notably astrocytes, leading to neurodegenerative processes, such as Alzheimer (AD) and Parkinson diseases (PD). In this study, we performed for the first time, a whole lipidomic characterization of Normal Human Astrocytes cultures exposed to toxic concentrations of palmitic acid and the protective compound tibolone, to establish and identify the set of potential metabolites that are modulated under these experimental treatments. The study covered 3843 features involved in the exo- and endo-metabolome extracts obtained from astrocytes with the mentioned treatments. Through multivariate statistical analysis such as PCA (principal component analysis), partial least squares (PLS-DA), clustering analysis, and machine learning enrichment analysis, it was possible to determine the specific metabolites that were affected by palmitic acid insult, such as phosphoethanolamines, phosphoserines phosphocholines and glycerophosphocholines, with their respective metabolic pathways impact. Moreover, our results suggest the importance of tibolone in the generation of neuroprotective metabolites by astrocytes and may be relevant to the development of neurodegenerative processes.

LPS-induced lipid alterations in microglia revealed by MALDI mass spectrometry-based cell fingerprinting in neuroinflammation studies

Pathological microglia activation can promote neuroinflammation in many neurodegenerative diseases, and it has therefore emerged as a potential therapeutic target. Increasing evidence suggests alterations in lipid metabolism as modulators and indicators in microglia activation and its effector functions. Yet, how lipid dynamics in activated microglia is affected by inflammatory stimuli demands additional investigation to allow development of more effective therapies. Here, we report an extensive matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) whole cell fingerprinting workflow to investigate inflammation-associated lipid patterns in SIM-A9 microglial cells. By combining a platform of three synergistic MALDI MS technologies we could detect substantial differences in lipid profiles of lipopolysaccharide (LPS)- stimulated and unstimulated microglia-like cells leading to the identification of 21 potential inflammation-associated lipid markers. LPS-induced lipids in SIM-A9 microglial cells include phosphatidylcholines, lysophosphatidylcholines (LysoPC), sphingolipids, diacylglycerols and triacylglycerols. Moreover, MALDI MS-based cell lipid fingerprinting of LPS-stimulated SIM-A9 microglial cells pre-treated with the non-selective histone deacetylase inhibitor suberoylanilide hydroxamic acid revealed specific modulation of LPS-induced-glycerolipids and LysoPC(18:0) with a significant reduction of microglial inflammation response. Our study introduces MALDI MS as a complementary technology for fast and label-free investigation of stimulus-dependent changes in lipid patterns and their modulation by pharmaceutical agents.

Intestinal Microbiota Remodeling Protects Mice from Western Diet-Induced Brain Inflammation and Cognitive Decline

It has been shown that the Western diet (WD) induces systemic inflammation and cognitive decline. Moreover, probiotic supplementation and antibiotic treatment reduce diet-induced hepatic inflammation. The current study examines whether shaping the gut microbes by Bifidobacterium infantis (B. infantis) supplementation and antibiotic treatment reduce diet-induced brain inflammation and improve neuroplasticity. Furthermore, the significance of bile acid (BA) signaling in regulating brain inflammation was studied. Mice were fed a control diet (CD) or WD for seven months. B. infantis was supplemented to WD-fed mice to study brain inflammation, lipid, metabolomes, and neuroplasticity measured by long-term potentiation (LTP). Broad-spectrum coverage antibiotics and cholestyramine treatments were performed to study the impact of WD-associated gut microbes and BA in brain inflammation. Probiotic B. infantis supplementation inhibited diet-induced brain inflammation by reducing IL6, TNFα, and CD11b levels. B. infantis improved LTP and increased brain PSD95 and BDNF levels, which were reduced due to WD intake. Additionally, B. infantis reduced cecal cholesterol, brain ceramide and enhanced saturated fatty acids. Moreover, antibiotic treatment, as well as cholestyramine, diminished WD-induced brain inflammatory signaling. Our findings support the theory that intestinal microbiota remodeling by B. infantis reduces brain inflammation, activates BA receptor signaling, and improves neuroplasticity.

Fat and Protein Combat Triggers Immunological Weapons of Innate and Adaptive Immune Systems to Launch Neuroinflammation in Parkinson's Disease

Parkinson's disease (PD) is the second-most common neurodegenerative disease in the world, affecting up to 10 million people. This disease mainly happens due to the loss of dopaminergic neurons accountable for memory and motor function. Partial glucocerebrosidase enzyme deficiency and the resultant excess accumulation of glycosphingolipids and alpha-synuclein (α-syn) aggregation have been linked to predominant risk factors that lead to neurodegeneration and memory and motor defects in PD, with known and unknown causes. An increasing body of evidence uncovers the role of several other lipids and their association with α-syn aggregation, which activates the innate and adaptive immune system and sparks brain inflammation in PD. Here, we review the emerging role of a number of lipids, i.e., triglyceride (TG), diglycerides (DG), glycerophosphoethanolamines (GPE), polyunsaturated fatty acids (PUFA), sphingolipids, gangliosides, glycerophospholipids (GPL), and cholesterols, and their connection with α-syn aggregation as well as the induction of innate and adaptive immune reactions that trigger neuroinflammation in PD.

Punicic Acid and Its Role in the Prevention of Neurological Disorders: A Review

Millions of people worldwide are affected by neurodegenerative diseases (NDs). NDs are characterized by progressive damage and death of nerve cells accompanied by high levels of inflammatory biomarkers and oxidative stress conditions. Punicic acid, the main bioactive component of pomegranate (Punica granatum) seed oil, is an omega-5 isomer of conjugated α-linoleic acid that has shown strong anti-oxidative and anti-inflammatory effects that contributes towards its positive effect against a wide arrange of diseases. Punicic acid decreases oxidative damage and inflammation by increasing the expression of peroxisome proliferator-activated receptors. In addition, it can reduce beta-amyloid deposits formation and tau hyperphosphorylation by increasing the expression of GLUT4 protein and the inhibition of calpain hyperactivation. Microencapsulated pomegranate, with high levels of punicic acid, increases antioxidant PON1 activity in HDL. Likewise, encapsulated pomegranate formulations with high levels of punicic acid have shown an increase in the antioxidant PON1 activity in HDL. Because of the limited brain permeability of punicic acid, diverse delivery formulations have been developed to enhance the biological activity of punicic acid in the brain, diminishing neurological disorders symptoms. Punicic acid is an important nutraceutical compound in the prevention and treatment of neurodegenerative diseases such as Alzheimer's, Parkinson's, and Huntington's disease.

The Impact of the hAPP695SW Transgene and Associated Amyloid-β Accumulation on Murine Hippocampal Biochemical Pathways

Background: Alzheimer’s disease (AD) is a neurodegenerative disease characterized by the accumulation of amyloid-β (Aβ) peptide in the brain. Objective: Gain a better insight into alterations in major biochemical pathways underlying AD. Methods: We compared metabolomic profiles of hippocampal tissue of 20-month-old female Tg2576 mice expressing the familial AD-associated hAPP695SW transgene with their 20-month-old wild type female littermates. Results: The hAPP695SW transgene causes overproduction and accumulation of Aβ in the brain. Out of 180 annotated metabolites, 54 metabolites differed (30 higher and 24 lower in Tg2576 versus wild-type hippocampal tissue) and were linked to the amino acid, nucleic acid, glycerophospholipid, ceramide, and fatty acid metabolism. Our results point to 1) heightened metabolic activity as indicated by higher levels of urea, enhanced fatty acid β-oxidation, and lower fatty acid levels; 2) enhanced redox regulation; and 3) an imbalance of neuro-excitatory and neuro-inhibitory metabolites in hippocampal tissue of aged hAPP695SW transgenic mice. Conclusion: Taken together, our results suggest that dysregulation of multiple metabolic pathways associated with a concomitant shift to an excitatory-inhibitory imbalance are contributing mechanisms of AD-related pathology in the Tg2576 mouse.

A Machine Learning-Based Holistic Approach to Predict the Clinical Course of Patients within the Alzheimer's Disease Spectrum

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative condition driven by multifactorial etiology. Mild cognitive impairment (MCI) is a transitional condition between healthy aging and dementia. No reliable biomarkers are available to predict the conversion from MCI to AD.

OBJECTIVE

To evaluate the use of machine learning (ML) on a wealth of data offered by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Alzheimer's Disease Metabolomics Consortium (ADMC) database in the prediction of the MCI to AD conversion.

METHODS

We implemented an ML-based Random Forest (RF) algorithm to predict conversion from MCI to AD. Data related to the study population (587 MCI subjects) were analyzed by RF as separate or combined features and assessed for classification power. Four classes of variables were considered: neuropsychological test scores, AD-related cerebrospinal fluid (CSF) biomarkers, peripheral biomarkers, and structural magnetic resonance imaging (MRI) variables.

RESULTS

The ML-based algorithm exhibited 86% accuracy in predicting the AD conversion of MCI subjects. When assessing the features that helped the most, neuropsychological test scores, MRI data, and CSF biomarkers were the most relevant in the MCI to AD prediction. Peripheral parameters were effective when employed in association with neuropsychological test scores. Age and sex differences modulated the prediction accuracy. AD conversion was more effectively predicted in females and younger subjects.

CONCLUSION

Our findings support the notion that AD-related neurodegenerative processes result from the concerted activity of multiple pathological mechanisms and factors that act inside and outside the brain and are dynamically affected by age and sex.

New insights into human prefrontal cortex aging with a lipidomics approach

INTRODUCTION

Human prefrontal cortex (hPFC) is a recent evolutionarily developed brain region involved in cognitive functions. Human cognitive functions decline during aging. Yet the molecular mechanisms underlying the functional deterioration of the neural cells of this brain region still remain to be fully described.

AREAS COVERED

In this review, we explore the role of lipids in hPFC aging. Firstly, we briefly consider the approaches used to identify lipid species in brain tissue with special attention paid to a lipidomics analysis. Then, as the evolution process has conferred a specific lipid profile on the hPFC, we consider the lipidome of hPFC. In addition, the role of lipids in hPFC aging, and in particular, the cognitive decline associated with aging, is discussed. Finally, nutritional and pharmacological interventions designed to modulate this process are examined. It is suggested that the dysfunction of key cellular processes secondarily to the damage of lipid membrane underlies the cognitive decline of hPFC during aging.

EXPERT OPINION

Lipidomics methods are and will continue to be key tools in the effort to gain additional insights into the aging of the human brain.