Predictive Modeling of Alzheimer's and Parkinson's Disease Using Metabolomic and Lipidomic Profiles from Cerebrospinal Fluid

The Role of Alpha-Synuclein in Synucleinopathy: Impact on Lipid Regulation at Mitochondria-ER Membranes

The protein alpha-synuclein (αSyn) plays a critical role in the pathogenesis of synucleinopathy, which includes Parkinson's disease and multiple system atrophy, and mounting evidence suggests that lipid dyshomeostasis is a critical phenotype in these neurodegenerative conditions. Previously, we identified that αSyn localizes to mitochondria-associated endoplasmic reticulum membranes (MAMs), temporary functional domains containing proteins that regulate lipid metabolism, including the de novo synthesis of phosphatidylserine. In the present study, we have analyzed the lipid composition of postmortem human samples, focusing on the substantia nigra pars compacta of Parkinson's disease and controls, as well as three less affected brain regions of Parkinson's donors. To further assess synucleinopathy-related lipidome alterations, similar analyses were performed on the striatum of multiple system atrophy cases. Our data show region-and disease-specific changes in the levels of lipid species. Specifically, our data revealed alterations in the levels of specific phosphatidylserine species in brain areas most affected in Parkinson's disease. Some of these alterations, albeit to a lesser degree, are also observed multiples system atrophy. Using induced pluripotent stem cell-derived neurons, we show that αSyn contributes to regulating phosphatidylserine metabolism at MAM domains, and that αSyn dosage parallels the perturbation in phosphatidylserine levels. Our results support the notion that αSyn pathophysiology is linked to the dysregulation of lipid homeostasis, which may contribute to the vulnerability of specific brain regions in synucleinopathy. These findings have significant therapeutic implications.

Untargeted serum metabolic profiling of diabetes mellitus among Parkinson's disease patients

Type 2 diabetes mellitus (T2DM) is a common comorbidity among Parkinson's disease (PD) patients. Yet, little is known about dysregulated pathways that are unique in PD patients with T2DM. We applied high-resolution metabolomic profiling in serum samples of 636 PD and 253 non-PD participants recruited from Central California. We conducted an initial discovery metabolome-wide association and pathway enrichment analysis. After adjusting for multiple testing, in positive (or negative) ion mode, 30 (25) metabolic features were associated with T2DM in both PD and non-PD participants, 162 (108) only in PD participants, and 32 (7) only in non-PD participants. Pathway enrichment analysis identified 17 enriched pathways associated with T2DM in both the PD and non-PD participants, 26 pathways only in PD participants, and 5 pathways only in non-PD participants. Several amino acid, nucleic acids, and fatty acid metabolisms were associated with T2DM only in the PD patient group suggesting a possible link between PD and T2DM.

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.

Integrated metabolomics and proteomics analysis of plasma lipid metabolism in Parkinson's disease

INTRODUCTION

Metabolomics and proteomics are two growing fields of science which may shed light on the molecular mechanisms that contribute to neurodegenerative diseases. Studies focusing on these aspects can reveal specific metabolites and proteins that can halt or reverse the progressive neurodegenerative process leading to dopaminergic cell death in the brain.

AREAS COVERED

In this article, an overview of the current status of metabolomic and proteomic profiling in the neurodegenerative disease such as Parkinson's disease (PD) is presented. We discuss the importance of state-of-the-art metabolomics and proteomics using advanced analytical methodologies and their potential for discovering new biomarkers in PD. We critically review the research to date, highlighting how metabolomics and proteomics can have an important impact on early disease diagnosis, future therapy development and the identification of new biomarkers. Finally, we will discuss interactions between lipids and α-synuclein (SNCA) and also consider the role of SNCA in lipid metabolism.

EXPERT OPINION

Metabolomic and proteomic studies contribute to understanding the biological basis of PD pathogenesis, identifying potential biomarkers and introducing new therapeutic strategies. The complexity and multifactorial nature of this disease requires a comprehensive approach, which can be achieved by integrating just these two omic studies.

Exploring the interplay between metabolomics and genetics in Parkinson's disease: Insights from ongoing research and future avenues

Parkinson's disease (PD) is a widespread neurodegenerative disorder, whose complex aetiology remains under construction. While rare variants have been associated with the monogenic PD form, most PD cases are influenced by multiple genetic and environmental aspects. Nonetheless, the pathophysiological pathways and molecular networks involved in monogenic/idiopathic PD overlap, and genetic variants are decisive in elucidating the convergent underlying mechanisms of PD. In this scenario, metabolomics has furnished a dynamic and systematic picture of the synergy between the genetic background and environmental influences that impact PD, making it a valuable tool for investigating PD-related metabolic dysfunctions. In this review, we performed a brief overview of metabolomics current research in PD, focusing on significant metabolic alterations observed in idiopathic PD from different biofluids and strata and exploring how they relate to genetic factors associated with monogenic PD. Dysregulated amino acid metabolism, lipid metabolism, and oxidative stress are the critical metabolic pathways implicated in both genetic and idiopathic PD. By merging metabolomics and genetics data, it is possible to distinguish metabolic signatures of specific genetic backgrounds and to pinpoint subgroups of PD patients who could derive personalized therapeutic benefits. This approach holds great promise for advancing PD research and developing innovative, cost-effective treatments.

Clinical lipidomics in the era of the big data

Lipidomics as a branch of metabolomics provides unique information on the complex lipid profile in biological materials. In clinically focused studies, hundreds of lipids together with available clinical information proved to be an effective tool in the discovery of biomarkers and understanding of pathobiochemistry. However, despite the introduction of lipidomics nearly twenty years ago, only dozens of big data studies using clinical lipidomics have been published to date. In this review, we discuss the lipidomics workflow, statistical tools, and the challenges of standartisation. The consequent summary divided into major clinical areas of cardiovascular disease, cancer, diabetes mellitus, neurodegenerative and liver diseases is demonstrating the importance of clinical lipidomics. In these publications, the potential of lipidomics for prediction, diagnosis or finding new targets for the treatment of selected diseases can be seen. The first of these results have already been implemented in clinical practice in the field of cardiovascular diseases, while in other areas we can expect the application of the results summarized in this review in the near future.

Diagnostic metabolomic profiling of Parkinson's disease biospecimens

BACKGROUND

Reliable and sensitive biomarkers are needed for enhancing and predicting Parkinson's disease (PD) diagnosis.

OBJECTIVE

To investigate comprehensive metabolomic profiling of biochemicals in CSF and serum for determining diagnostic biomarkers of PD.

METHODS

Fifty subjects, symptomatic with PD for ≥5 years, were matched to 50 healthy controls (HCs). We used ultrahigh-performance liquid chromatography linked to tandem mass spectrometry (UHPLC-MS/MS) for measuring relative concentrations of ≤1.5 kDalton biochemicals. A reference library created from authentic standards facilitated chemical identifications. Analytes underwent univariate analysis for PD association, with false discovery rate-adjusted p-value (≤0.05) determinations. Multivariate analysis (for identifying a panel of biochemicals discriminating PD from HCs) used several biostatistical methods, including logistic LASSO regression.

RESULTS

Comparing PD and HCs, strong differentiation was achieved from CSF but not serum specimens. With univariate analysis, 21 CSF compounds exhibited significant differential concentrations. Logistic LASSO regression led to selection of 23 biochemicals (11 shared with those determined by the univariate analysis). The selected compounds, as a group, distinguished PD from HCs, with Area-Under-the-Receiver-Operating-Characteristic (ROC) curve of 0.897. With optimal cutoff, logistic LASSO achieved 100% sensitivity and 96% specificity (and positive and negative predictive values of 96% and 100%). Ten-fold cross-validation gave 84% sensitivity and 82% specificity (and 82% positive and 84% negative predictive values). From the logistic LASSO-chosen regression model, 2 polyamine metabolites (N-acetylcadaverine and N-acetylputrescine) were chosen and had the highest fold-changes in comparing PD to HCs. Another chosen biochemical, acisoga (N-(3-acetamidopropyl)pyrrolidine-2-one), also is a polyamine metabolism derivative.

CONCLUSIONS

UHPLC-MS/MS assays provided a metabolomic signature highly predictive of PD. These findings provide further evidence for involvement of polyamine pathways in the neurodegeneration of PD.

Lipid profiles in the cerebrospinal fluid of rats with 6-hydroxydopamine-induced lesions as a model of Parkinson's disease

Background

Parkinson's disease (PD) is a progressive neurodegenerative disease with characteristic pathological abnormalities, including the loss of dopaminergic (DA) neurons, a dopamine-depleted striatum, and microglial activation. Lipid accumulation exhibits a close relationship with these pathologies in PD.

Methods

Here, 6-hydroxydopamine (6-OHDA) was used to construct a rat model of PD, and the lipid profile in cerebrospinal fluid (CSF) obtained from model rats was analyzed using lipidomic approaches.

Results

Establishment of this PD model was confirmed by apomorphine-induced rotation behaviors, loss of DA neurons, depletion of dopamine in the striatum, and microglial activation after 6-OHDA-induced lesion generation. Unsupervised and supervised methods were employed for lipid analysis. A total of 172 lipid species were identified in CSF and subsequently classified into 18 lipid families. Lipid families, including eicosanoids, triglyceride (TG), cholesterol ester (CE), and free fatty acid (FFA), and 11 lipid species exhibited significantly altered profiles 2 weeks after 6-OHDA administration, and significant changes in eicosanoids, TG, CE, CAR, and three lipid species were noted 5 weeks after 6-OHDA administration. During the period of 6-OHDA-induced lesion formation, the lipid families and species showed concentration fluctuations related to the recovery of behavior and nigrostriatal abnormalities. Correlation analysis showed that the levels of eicosanoids, CE, TG families, and TG (16:0_20:0_18:1) exhibited positive relationships with apomorphine-induced rotation behaviors and negative relationships with tyrosine hydroxylase (TH) expression in the midbrain.

Conclusion

These results revealed that non-progressive nigrostriatal degeneration induced by 6-OHDA promotes the expression of an impairment-related lipidomic signature in CSF, and the level of eicosanoids, CE, TG families, and TG (16:0_20:0_18:1) in CSF may reveal pathological changes in the midbrain after 6-OHDA insult.

Serum vitamin levels in multiple system atrophy: A case-control study

Aim

There is increasing evidence suggesting that vitamins may play important roles in the pathogenesis of multiple system atrophy (MSA). The purpose of this study was to detect the changes of serum vitamin levels and investigate their correlation with disease severity in MSA patients.

Methods

In this cross-sectional study, 244 MSA patients, 200 Parkinson's disease (PD) patients and 244 age-gender matched healthy controls were recruited. Serum vitamin levels were measured, including vitamin A, B1, B2, B9 (folate), B12, C, D, and E. Relevant clinical scales were used to assess the disease severity of MSA patients.

Results

Compared with the healthy controls, decreased serum folate levels and increased serum vitamin A and C levels were detected in MSA patients. Similar differences were also observed in the gender-based subgroup analysis. There were no differences detected between MSA and PD patients. In MSA patients, significant correlation was found between vitamin A, folate, or vitamin C and relevant clinical scales or laboratory findings. In addition, ROC analysis showed potential diagnostic value of the combination of vitamin A, folate, and vitamin C in distinguishing MSA patients from healthy controls.

Conclusion

There were significant changes in the blood vitamin spectrums of MSA patients, suggesting that dysregulation of vitamins homeostasis might play an important role in the pathogenesis of MSA.

Serum Phospholipid Profile Changes in Gaucher Disease and Parkinson's Disease

Alterations in the levels of serum sphingolipids and phospholipids have been reported in Gaucher disease and in Parkinson's disease, suggesting a potential role of these lipids as biomarkers. This project's objective is to detect novel associations and novel candidate biomarkers in the largest Spanish Gaucher and Parkinson diseases of the Iberian Peninsula. For that, 278 participants were included: 100 sporadic Parkinson's patients, 70 Gaucher patients, 15 GBA1-mutation-carrier Parkinson's patients and 93 controls. A serum lipidomics array including 10 phospholipid groups, 368 species, was performed using high-performance liquid chromatography-mass spectrometry. Lipid levels were compared between groups via multiple-regression analyses controlling for clinical and demographic parameters. Additionally, lipid levels were compared within the Gaucher and Parkinson's groups controlling for medication and/or disease severity. Results were controlled for robustness by filtering of non-detectable lipid values. There was an increase in the levels of phosphatidylcholine, with a simultaneous decrease in lyso-phosphatidylcholine, in the Gaucher, Parkinson's and GBA1-mutation-carrier Parkinson's patients vs. controls. Phosphatidylethanolamine, lyso- and plasmalogen-phosphatidylethanolamine were also increased in Gaucher and Parkinson's. Gaucher patients also showed an increase in lyso-phosphatidylserine and phosphatidylglycerol. While in the Gaucher and Parkinson's groups, velaglucerase alpha and dopamine agonists, respectively, showed positive associations with the lipid changes, miglustat treatment in Gaucher patients normalized the altered phosphatidylcholine/lyso-phosphatidylcholine ratio. In conclusion, Gaucher and Parkinson's patients showed changes in various serum phospholipid levels when compared with healthy controls, further supporting the role of such lipids in disease development and, possibly, as putative biomarkers. This hypothesis was reinforced by the normalizing effect of miglustat, and by controlling for data robustness, even though the limited number of participants, especially in the sub-distribution by treatment groups in GD requires validation in a larger number of patients.