Project description:This project is about an untargeted metabolomic analysis in samples that come from chronic lung allograft dysfunction disease patients.
Project description:Background and aims: Gene mutations or variants leading to insufficient reactive oxygen species (ROS) production have been associated with inflammatory bowel disease (IBD). In particular, 40-50% of patients with chronic granulomatous disease have IBD (CGD-IBD). CGD is caused by inherited defects in any one of the 5 subunits forming the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase complex 2 (NOX2), leading to severely reduced or absent phagocyte-derived ROS production. While conventional IBD therapies can treat CGD-IBD, their benefits must be weighed against the risk of infection in this immune compromised population. Understanding the impact of NOX2 defects on the composition and function of the intestinal microbiota may lead to the identification of treatments for CGD-IBD. Methods: We evaluated GI symptom and quality of life scores, and clinical biomarkers of local (i.e. fecal occult blood and calprotectin) and systemic (i.e. CBC, CRP, ESR, and albumin) inflammation in a cohort of 79 patients with CGD, 8 mutation carriers and 17 healthy controls followed at the National Institutes of Health (NIH). We profiled the intestinal microbiome by 16S rRNA (V4 region) sequencing and the stool metabolome by mass spectrometry in all fecal samples, and further validated our findings by profiling the stool microbiome in a second cohort of 36 patients with CGD recruited from 11 centers across North-America through the Primary Immune Deficiency Treatment Consortium (PIDTC). Predictive functional profiling of the microbial communities based on 16S rRNA sequencing was also performed. Results: After controlling for significant variables, we show decreased alpha diversity and identified distinct intestinal microbiome and metabolomic profiles in patients with CGD compared to healthy individuals. In particular, we observed enrichment for Erysipelatoclostridium spp., Sellimonas spp. and Lachnoclostridium spp. in stool samples from patients with CGD. Despite differences in alpha and beta diversity in samples from the NIH compared to the PIDTC cohort, there were several bacterial taxa that correlated significantly between both cohorts. We further demonstrate that patients with active IBD and/or a history of IBD have a distinct microbiome and metabolomic profile compared to patients without CGD-IBD and identified bacterial taxa to be evaluated as potential markers of disease severity, as well as targets for future therapeutic interventions. Conclusions: Intestinal microbiome and metabolomic signatures distinguished patients with CGD and CGD-IBD and identified microbial and metabolomic candidates to be further evaluated as potential targets to improve the management of patients with CGD-IBD.
Project description:Sugarcane smut disease, caused by the biotrophic fungus Sporisorium scitamineum, is characterized by the development of a whip-like structure from the plant meristem. The disease causes negative effects on sucrose accumulation, fiber content and juice quality. The aim of this study was to exam whether the transcriptomic changes already described during the infection of sugarcane by S. scitamineum result in changes at the metabolomic level. To address this question, an analysis was conducted during the initial stage of the interaction and through disease progression in a susceptible sugarcane genotype. GC-TOF-MS allowed the identification of 73 primary metabolites. A set of these compounds was quantitatively altered at each analyzed point as compared with healthy plants. The results revealed that energetic pathways and amino acid pools were affected throughout the interaction. Raffinose levels increased shortly after infection but decreased remarkably after whip emission. Changes related to cell wall biosynthesis were characteristic of disease progression and suggested a loosening of its structure to allow whip growth. Lignin biosynthesis related to whip formation may rely on Tyr metabolism through the overexpression of a bifunctional PTAL. The altered levels of Met residues along with overexpression of SAM synthetase and ACC synthase genes suggested a role for ethylene in whip emission. Moreover, unique secondary metabolites antifungal-related were identified using LC-ESI-MS approach, which may have potential biomarker applications. Lastly, a putative toxin was the most important fungal metabolite identified whose role during infection remains to be established.
Project description:Mild cognitive impairment (MCI) is considered as a transition phase between normal aging and Alzheimer's disease (AD). MCI confers an increased risk of developing AD, although the state is heterogeneous with several possible outcomes, including even improvement back to normal cognition. We sought to determine the serum metabolomic profiles associated with progression to and diagnosis of AD in a prospective study. At the baseline assessment, the subjects enrolled in the study were classified into three diagnostic groups: healthy controls (n=46), MCI (n=143) and AD (n=47). Among the MCI subjects, 52 progressed to AD in the follow-up. Comprehensive metabolomics approach was applied to analyze baseline serum samples and to associate the metabolite profiles with the diagnosis at baseline and in the follow-up. At baseline, AD patients were characterized by diminished ether phospholipids, phosphatidylcholines, sphingomyelins and sterols. A molecular signature comprising three metabolites was identified, which was predictive of progression to AD in the follow-up. The major contributor to the predictive model was 2,4-dihydroxybutanoic acid, which was upregulated in AD progressors (P=0.0048), indicating potential involvement of hypoxia in the early AD pathogenesis. This was supported by the pathway analysis of metabolomics data, which identified upregulation of pentose phosphate pathway in patients who later progressed to AD. Together, our findings primarily implicate hypoxia, oxidative stress, as well as membrane lipid remodeling in progression to AD. Establishment of pathogenic relevance of predictive biomarkers such as ours may not only facilitate early diagnosis, but may also help identify new therapeutic avenues.
Project description:Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive fibrosing interstitial lung disease that is unresponsive to current therapy. While it carries a median survival of less than 3 years its rate of progression varies widely between patients. We hypothesized that studying the gene expression profiles of physiologically stable patients and those in which the disease progressed rapidly after the initial diagnosis would aid in the search for biomarkers and contribute to the understanding of disease pathogenesis. We generated 12 Idiopathic Pulmonary Fibrosis (IPF) lung parenchyma SAGE profiles. Initial cluster analysis including 8 other public available lung SAGE libraries verified that the IPF transcriptome is distinct from normal lung tissue and other lung diseases like COPD. In order to identify candidate markers of disease progression we segregated the IPF SAGE profiles in two groups based on clinical parameters regarding lung volume and lung function.
Project description:Caffeine is the most widely consumed psychoactive substance worldwide. Strikingly, molecular pathways engaged by its regular consumption remain unclear. We herein addressed the mechanisms associated with habitual (chronic) caffeine consumption in the mouse hippocampus using untargeted orthogonal-omics techniques. Our results revealed that chronic caffeine exerts concerted pleiotropic effects in the hippocampus, at the epigenomic, proteomic and metabolomic levels, lowered metabolic-related processes in bulk tissue, while inducing neuronal-specific epigenetic changes at synaptic transmission/neuronal activity-related genes. Altogether, these findings suggest that regular intake of caffeine improves the signal-to-noise ratio during information encoding in learning in part through a re-setting of metabolic genes helping to bolster the salience of information processing in neuronal circuits.
Project description:Alzheimer's disease (AD) is the leading cause of dementia; however, men and women face differential AD prevalence, presentation, and progression risks. Characterizing metabolomic profiles during AD progression is fundamental to understand the metabolic disruptions and the biological pathways involved. However, outstanding questions remain of whether peripheral metabolic changes occur equally in men and women with AD. Here, we evaluated differential effects of metabolomic and brain volume associations between sexes. We used three cohorts from the Alzheimer's Disease Neuroimaging Initiative (ADNI), evaluated 1,368 participants, two metabolomic platforms with 380 metabolites in total, and six brain segment volumes. Using dimension reduction techniques, we took advantage of the correlation structure of the brain volume phenotypes and the metabolite concentration values to reduce the number of tests while aggregating relevant biological structures. Using WGCNA, we aggregated modules of highly co-expressed metabolites. On the other hand, we used partial least squares regression-discriminant analysis (PLS-DA) to extract components of brain volumes that maximally co-vary with AD diagnosis as phenotypes. We tested for differences in effect sizes between sexes in the association between single metabolite and metabolite modules with the brain volume components. We found five metabolite modules and 125 single metabolites with significant differences between sexes. These results highlight a differential lipid disruption in AD progression between sexes. Men showed a greater negative association of phosphatidylcholines and sphingomyelins and a positive association of VLDL and large LDL with AD progression. In contrast, women showed a positive association of triglycerides in VLDL and small and medium LDL with AD progression. Explicitly identifying sex differences in metabolomics during AD progression can highlight particular metabolic disruptions in each sex. Our research study and strategy can lead to better-tailored studies and better-suited treatments that take sex differences into account.
Project description:Rationale: Sepsis is a leading cause of morbidity and mortality; early diagnosis and prediction of progression is difficult to determine. The integration of metabolomic and transcriptomic data in an experimental model of sepsis may be a novel method to identify molecular signatures of clinical sepsis. Objectives: Develop a biomarker panel for earlier diagnosis and prognostic characterization of sepsis patients to inform personalized clinical management and improve understanding of the pathophysiology of sepsis progression. Methods: Mild to severe sepsis, lung injury and death was recapitulated in Macaca fascicularis by intravenous inoculation of Escherichia coli. Plasma samples were obtained at time of challenge and at one, three, and five days later or time of euthanasia. Necropsy was performed and blood, lung, kidney and spleen samples were obtained. An integrative analysis of comprehensive metabolomic and transcriptomic datasets was performed to identify and parameterize a biomarker panel. Measurements and Main Results: Pathogen invasion, respiratory distress, lethargy and mortality was dose dependent. Severe infection and death were associated with metabolomic and transcriptomic changes indicative of mitochondrial, peroxisomal and liver dysfunction. Analysis of reciprocal pulmonary transcriptome and plasma metabolome data revealed an integrated host response that suggested dysregulated fatty acid catabolism resulting from peroxisome-proliferator activated receptor signaling. A representative 4-metabolite model effectively diagnosed sepsis in primates (AUC 0.966) and in two human sepsis cohorts (AUC=0.78 and 0.82). Conclusion: A model to guide early management of patients with sepsis was developed by analysis of reciprocal metabolomic and transcriptomic data in primates that diagnosed sepsis in humans. Transcriptomic analysis of lungs from Cynomolgus macaques challenged with E. coli