MetaboLights

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ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12746/m_MTBLS12746_NMR___metabolite_profiling_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12746/a_MTBLS12746_NMR___metabolite_profiling.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12746/s_MTBLS12746.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12746/i_Investigation.txtprimaryOK200ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12746Manual adjustments for phase and baseline were made for profiling analysis. Resonance assignments used Chenomx software, and metabolite quantification was performed with Bayesil software. (Marino, 2022) (Fig S1)     MetaboLightsPublicNuclear Magnetic Resonance (NMR) -Sex differences modulate blood metabolome profiles in Parkinson’s disease patients harbouring rare genetic variants.For calibration and measurement of NMR, we utilised trimethylsilyl propionic acid sodium salt (0.1% TSP in D2O) as an internal reference signal. NMR studies were conducted on a Bruker DRX600 MHz spectrometer (Bruker, Karlsruhe, Germany), using a 5 mm triple-resonance z-gradient TXI Probe. We used TOPSPIN version 3.2 for control and data analysis of the spectrometer (Bruker Biospin, Fällanden, Switzerland).  University of SalernoCarmen Marinoblood serumNMR spectroscopy assayBlood sampling was performed after a 6-h fasting. Whole blood was collected by peripheral venepuncture into clot activator tubes and gently mixed.Sample was stored upright for 30 min at room temperature to allow blood to clot, and centrifuged at 2000 ×g for 10 min at room temperature. Serum was aliquoted (0.5 ml) in polypropylene cryotubes and stored at −80C before usage. Unique anonymized codes have been assigned to the samples for processing and subsequent analysis, maintaining the confidentiality of personal data.Homo sapienshttps://www.ebi.ac.uk/metabolights/MTBLS12746Alessandro Usiello. Ceinge Biotecnologie Avanzate (Italy). usiello@ceinge.unina.it.Carmen Marino. cmarino@unisa.it.The concentration matrices obtained from NMR peak quantifications were analysed using a univariate approach, combining a T-test with fold change analysis represented in a robust volcano plot. A fold change threshold of 1 and a p-value threshold of less than 0.05 were set     (Kumar et al., 2018) The matrices were normalised using sum and Pareto scaling before analysis. Partial least-squares discriminant analysis (PLS-DA) was performed on the normalised metabolomics data using MetaboAnalyst 6.0 (http://www.metaboanalyst.ca/). GenotypeGendercmarino@unisa.itOne-hundred forty healthy controls (HC) and two-hundred twelve PD patients were included in this study. Demographic and clinical features of participants are reported in Manuscript. In the PD cohort, 121 patients were classified as idiopathic (iPD; 65 male/56 female; Table 1), while 91 exhibited rare non-pathogenic mutations (rvPD; 44 male/47 female; Table 1). The age of HC participants ranged from 25 to 90 years, while patients with idiopathic PD and those with rare PD variants ranged from 48 to 82 years and 40 to 79 years, respectively. Acquiring the Carr-Purcell-Meiboom-Gill (CPMG) spectrum was crucial, as serum holds macromolecules like proteins that can disrupt signals from other sources metabolites. (Ghini et al., 2019) CPMG experiments employed a spectral width of 7 kHz along with 32k data points. A water presaturation was conducted for 5 seconds during the relaxation period, followed by a spin-echo delay of 0.3 ms. The time-domain data underwent a weighted Fourier transform with 0.5 Hz line broadeningMetabolomicsParkinson Diseasenuclear magnetic resonance spectroscopyGenetictargeted metabolitesParkinson Diseasenuclear magnetic resonance spectroscopyGenetictargeted metabolitesSerum samples were prepared in accordance with the NMR metabolomics sample quality preservation guidelines. (Marino et al., 2022)To prepare NMR samples, 150 μL of phosphate buffer (0.075 M Na2HPO4·7H2O, 4% NaN3, and water) was mixed with 150 μL of blood serum and subsequently transferred into a 3 mm NMR tube. TMAOL-ArginineTaurineD-FructoseD-GlucoseL-PhenylalanineLactate2-OxoglutarateCreatineD-FucoseD-MaltoseL-OrnithineL-IsoleucineD-MannoseL-AsparagineL-Glycine3-HydroxybutyrateValerateL-ThreonineBetaineL-AlanineL-CarnitineD-GalactoseAcetoacetateL-LeucineCreatinineMyo-InositolN-AcetylglycineL-GlutamicAcidL-CystinePyruvateGlycerolPyroglutamateL-ProlineL-GlutamineL-TyrosineGlucuronate2-HydroxyisovalerateL-SerineL-ValineL-AspartateGlycerophosphocholine2-Oxoisovalerate2-HydroxybutyratefalseSex differences modulate blood metabolome profiles in Parkinson’s disease patients harbouring rare genetic variantsBackground: Recent findings from our group indicate that sex differences in Parkinson's disease (PD) patients with idiopathic conditions or carrying pathogenic mutations significantly influence the blood occurrence of D and L-amino acids, lipids, antioxidants, and energy-related metabolites when compared to healthy controls (HC). In addition to pathogenic mutations, PD patients may also carry rare genetic variants of uncertain significance, whose effects on systemic metabolism have yet to be studied.Methods: We combined untargeted ¹H NMR -based metabolomics to detect broad serum biochemical alterations, with high-performance liquid chromatography (HPLC) analysis of D- and L-amino acids involved in NMDA receptor signaling. The serum metabolome were analyzed in a large cohort of genetically and clinically well-defined PD patients (n = 212) and a balanced group of healthy controls (HC, n = 140). PD patients included idiopathic cases (iPD, n = 121) and those carrying at least one rare variant (rvPD, n = 91) in the following susceptibility genes AIMP2, DNAJC13, DNAJC6, EIF4G1, FBXO7, GIPC1, HMOX2, HSPA8, HTRA2, IMMT, KIF21B, KIF24, LRRK2, MAN2C1, PRKN, RHOT2, SLC25A39, SLC6A3, SNCAIP, SPTBN1, TVP23A, UCHL1, VPS35, ZSCAN21.Results: Multivariate analysis (MVA) of NMR-based measurements identified notable differences between rvPD and HC groups, highlighting significant alterations in 18 metabolic pathways. Male rvPD patients displayed more extensive disruptions in cellular pathways, particularly in several amino acid and glutathione metabolism. In contrast, female patients showed fewer changes, primarily affecting lipid pathways. MVA did not distinguish serum metabolome profiles between iPD and rvPD in either sex, indicating shared biochemical changes in patients with various genetic backgrounds. Notably, HPLC confirmed a significant reduction in L-glutamate among male rvPD patients, a finding not seen in females compared to sex-matched HC. Additionally, L-serine and L-glutamate levels were correlated with MDS-UPDRS III scores in both sexes, with stronger associations observed in male rvPD patients. In line with remarkable alterations in glycine-serine metabolism, association analysis identified Serine Hydroxymethyltransferase 1 (SHMT1), Serine Hydroxymethyltransferase 2 (SHMT2) and Glycine cleavage system H protein, mitochondrial (GCSH) as genetic modifiers for rvPD patients stratified by gender.Conclusion: Our findings highlight the critical influence of sex and rare genetic variants in shaping serum metabolic signatures and their association with motor symptoms in Parkinson's disease.2026-06-262025-07-18MTBLS12746MTBLC64552MTBLC30915MTBLC16530MTBLC37054MTBLC13705MTBLC60645MTBLC17750MTBLC16919MTBLC16737MTBLC37714MTBLC28847MTBLC4139MTBLC4167MTBLC4153MTBLC18147MTBLC4208MTBLC17754MTBLC16870MTBLC24996MTBLC16977MTBLC16467MTBLC17196MTBLC17053MTBLC16347MTBLC16283MTBLC16015MTBLC18050MTBLC15428MTBLC17191MTBLC15603MTBLC15729MTBLC17295MTBLC17203MTBLC17115MTBLC16857MTBLC17895MTBLC16414MTBLC17268MTBLC40410MTBLC18183MTBLC15361MTBLC15891MTBLC15724MTBLC31011CHEBI:64552CHEBI:30915CHEBI:16530CHEBI:37054CHEBI:13705CHEBI:60645CHEBI:17750CHEBI:16919CHEBI:16737CHEBI:37714CHEBI:28847CHEBI:4139CHEBI:4167CHEBI:4153CHEBI:18147CHEBI:4208CHEBI:17754CHEBI:16870CHEBI:24996CHEBI:16977CHEBI:16467CHEBI:17196CHEBI:17053CHEBI:16347CHEBI:16283CHEBI:16015CHEBI:18050CHEBI:15428CHEBI:17191CHEBI:15603CHEBI:15729CHEBI:17295CHEBI:17203CHEBI:17115CHEBI:16857CHEBI:17895CHEBI:16414CHEBI:17268CHEBI:40410CHEBI:18183CHEBI:15361CHEBI:15891CHEBI:15724CHEBI:31011