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

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.

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.

Plasma Metabolic Analysis Reveals the Dysregulation of Short-Chain Fatty Acid Metabolism in Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder, characterized by high morbidity, high disability rate, and slow course of disease. The clinical diagnostic method of PD is complex and time-consuming, and there is no clear biomarker for clinical use. We aimed to investigate the plasma metabolites in PD and find out potential biomarkers with diagnostic ability. In the analysis of more than 40 metabolites including short-chain fatty acids, long-chain fatty acids, amino acids, and carbohydrates, the difference of short-chain fatty acids was observed. Acetic acid concentration was higher in PD than in healthy controls, and propanoic acid and 2,3,4-trihydroxybutyric acid were lower in PD. Compared with the early stage of PD, acetic acid increased significantly in the advanced stage of PD. Propanoic acid increased significantly in medicated PD compared with drug naïve PD. ROC analysis revealed acetic acid discriminated PD from healthy controls with 100% sensitivity, 88.9% specificity, and an area under the curve (AUC) of 0.981, and propanoic acid discriminated PD from healthy controls with an AUC of 0.981, 100% sensitivity, and 94.4% specificity. Acetic acid and propanoic acid may be a potential biomarker for differentiating PD from health, and the propanoic acid was evaluated as the most potential diagnostic marker because of its extremely high sensitivity and specificity.

Biomarker discovery in galactosemia: Metabolomics with UPLC/HRMS in dried blood spots

Introduction:Galactosemia (GAL) is a genetic disorder that results in disturbances in galactose metabolism and can lead to life-threatening complications. However, the underlying pathophysiology of long-term complications in GAL remains poorly understood. Methods: In this study, a metabolomics approach using ultra-performance liquid chromatography coupled with high-resolution mass spectrometry was used to investigate metabolomic changes in dried blood spots of 15 patients with GAL and 39 healthy individuals. Results: The study found that 2,819 metabolites underwent significant changes in patients with GAL compared to the control group. 480 human endogenous metabolites were identified, of which 209 and 271 were upregulated and downregulated, respectively. PA (8:0/LTE4) and ganglioside GT1c (d18:0/20:0) metabolites showed the most significant difference between GAL and the healthy group, with an area under the curve of 1 and 0.995, respectively. Additionally, the study identified potential biomarkers for GAL, such as 17-alpha-estradiol-3-glucuronide and 16-alpha-hydroxy DHEA 3-sulfatediphosphate. Conclusion: This metabolomics study deepened the understanding of the pathophysiology of GAL and presented potential biomarkers that might serve as prognostic biomarkers to monitor the progression or support the clinical diagnosis of GAL.