METHODS: We analysed plasma and urine samples of 50 stable CAD patients and 50 healthy controls using 1H NMR. Orthogonal partial least square discriminant analysis (OPLS-DA) followed by multivariate logistic regression (MVLR) models were developed to indicate the discriminating metabotypes. Metabolic pathway analysis was performed to identify the implicated pathways.
RESULTS: Both plasma and urine OPLS-DA models had specificity, sensitivity and accuracy of 100%, 96% and 98%, respectively. Plasma MVLR model had specificity, sensitivity, accuracy and AUROC of 92%, 86%, 89% and 0.96, respectively. The MVLR model of urine had specificity, sensitivity, accuracy and AUROC of 90%, 80%, 85% and 0.92, respectively. 35 and 12 metabolites were identified in plasma and urine metabotypes, respectively. Metabolic pathway analysis revealed that urea cycle, aminoacyl-tRNA biosynthesis and synthesis and degradation of ketone bodies pathways were significantly disturbed in plasma, while methylhistidine metabolism and galactose metabolism pathways were significantly disturbed in urine. The enrichment over representation analysis against SNPs-associated-metabolite sets library revealed that 85 SNPs were significantly enriched in plasma metabotype.
CONCLUSIONS: Cardiometabolic diseases, dysbiotic gut-microbiota and genetic variabilities are largely implicated in the pathogenesis of CAD.
METHODS: 1H-MRS utilising the Single-Voxel Spectroscopy (SVS) technique was performed using a 3.0Tesla MRI on 45 optic radiations (15 from healthy subjects, 15 from mild glaucoma patients, and 15 from severe glaucoma patients). A standardised Volume of Interest (VOI) of 20 × 20 × 20 mm was placed in the region of optic radiation. Mild and severe glaucoma patients were categorised based on the Hodapp-Parrish-Anderson (HPA) classification. Mean and multiple group comparisons for metabolite concentration and metabolite concentration ratio between glaucoma grades and healthy subjects were obtained using one-way ANOVA.
RESULTS: The metabolite concentration and metabolite concentration ratio between the optic radiations of glaucoma patients and healthy subjects did not demonstrate any significant difference (p > 0.05).
CONCLUSION: Our findings show no significant alteration of metabolite concentration associated with neurodegeneration that could be measured by single-voxel 1H-MRS in optic radiation among glaucoma patients.
KEY POINTS: • Glaucoma disease has a neurodegenerative component. • Metabolite changes have been observed in the neurodegenerative process in the brain. • Using SVS, no metabolite changes in optic radiation were attributed to glaucoma.
METHODS: Two hundred subjects (104 patients, 96 controls) underwent extensive clinical phenotyping. Stool samples were analyzed using 16S rRNA gene sequencing. Fecal metabolomics were performed using two platforms, nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry.
RESULTS: Fecal microbiome and metabolome composition in PD was significantly different from controls, with the largest effect size seen in NMR-based metabolome. Microbiome and NMR-based metabolome compositional differences remained significant after comprehensive confounder analyses. Differentially abundant fecal metabolite features and predicted functional changes in PD versus controls included bioactive molecules with putative neuroprotective effects (eg, short chain fatty acids [SCFAs], ubiquinones, and salicylate) and other compounds increasingly implicated in neurodegeneration (eg, ceramides, sphingosine, and trimethylamine N-oxide). In the PD group, cognitive impairment, low body mass index (BMI), frailty, constipation, and low physical activity were associated with fecal metabolome compositional differences. Notably, low SCFAs in PD were significantly associated with poorer cognition and low BMI. Lower butyrate levels correlated with worse postural instability-gait disorder scores.
INTERPRETATION: Gut microbial function is altered in PD, characterized by differentially abundant metabolic features that provide important biological insights into gut-brain pathophysiology. Their clinical relevance further supports a role for microbial metabolites as potential targets for the development of new biomarkers and therapies in PD. ANN NEUROL 2021;89:546-559.