ViLinh Tran

Plasma Metabolomics in Human Pulmonary Tuberculosis Disease: A Pilot Study

We aimed to characterize metabolites during tuberculosis (TB) disease and identify new pathophysiologic pathways involved in infection as well as biomarkers of TB onset, progression and resolution. Such data may inform development of new anti-tuberculosis drugs. Plasma samples from adults with newly diagnosed pulmonary TB disease and their matched, asymptomatic, sputum culture-negative household contacts were analyzed using liquid chromatography high-resolution mass spectrometry (LC-MS) to identify metabolites. Statistical and bioinformatics methods were used to select accurate mass/charge (m/z) ions that were significantly different between the two groups at a false discovery rate (FDR) of q<0.05. Two-way hierarchical cluster analysis (HCA) was used to identify clusters of ions contributing to separation of cases and controls, and metabolomics databases were used to match these ions to known metabolites. Identity of specific D-series resolvins, glutamate and Mycobacterium tuberculosis (Mtb)-derived trehalose-6-mycolate was confirmed using LC-MS/MS analysis. Over 23,000 metabolites were detected in untargeted metabolomic analysis and 61 metabolites were significantly different between the two groups. HCA revealed 8 metabolite clusters containing metabolites largely upregulated in patients with TB disease, including anti-TB drugs, glutamate, choline derivatives, Mycobacterium tuberculosis-derived cell wall glycolipids (trehalose-6-mycolate and phosphatidylinositol) and pro-resolving lipid mediators of inflammation, known to stimulate resolution, efferocytosis and microbial killing. The resolvins were confirmed to be RvD1, aspirin-triggered RvD1, and RvD2. This study shows that high-resolution metabolomic analysis can differentiate patients with active TB disease from their asymptomatic household contacts. Specific metabolites upregulated in the plasma of patients with active TB disease, including Mtb-derived glycolipids and resolvins, have potential as biomarkers and may reveal pathways involved in TB disease pathogenesis and resolution.

Serum Metabolomics of Slow vs. Rapid Motor Progression Parkinson’s Disease: a Pilot Study

Progression of Parkinson’s disease (PD) is highly variable, indicating that differences between slow and rapid progression forms could provide valuable information for improved early detection and management. Unfortunately, this represents a complex problem due to the heterogeneous nature of humans in regards to demographic characteristics, genetics, diet, environmental exposures and health behaviors. In this pilot study, we employed high resolution mass spectrometry-based metabolic profiling to investigate the metabolic signatures of slow versus rapidly progressing PD present in human serum. Archival serum samples from PD patients obtained within 3 years of disease onset were analyzed via dual chromatography-high resolution mass spectrometry, with data extraction by xMSanalyzer and used to predict rapid or slow motor progression of these patients during follow-up. Statistical analyses, such as false discovery rate analysis and partial least squares discriminant analysis, yielded a list of statistically significant metabolic features and further investigation revealed potential biomarkers. In particular, N8-acetyl spermidine was found to be significantly elevated in the rapid progressors compared to both control subjects and slow progressors. Our exploratory data indicate that a fast motor progression disease phenotype can be distinguished early in disease using high resolution mass spectrometry-based metabolic profiling and that altered polyamine metabolism may be a predictive marker of rapidly progressing PD.

Reference Standardization for Mass Spectrometry and High-resolution Metabolomics Applications to Exposome Research

The exposome is the cumulative measure of environmental influences and associated biological responses throughout the lifespan, including exposures from the environment, diet, behavior, and endogenous processes. A major challenge for exposome research lies in the development of robust and affordable analytic procedures to measure the broad range of exposures and associated biologic impacts occurring over a lifetime. Biomonitoring is an established approach to evaluate internal body burden of environmental exposures, but use of biomonitoring for exposome research is often limited by the high costs associated with quantification of individual chemicals. High-resolution metabolomics (HRM) uses ultra-high resolution mass spectrometry with minimal sample preparation to support high-throughput relative quantification of thousands of environmental, dietary, and microbial chemicals. HRM also measures metabolites in most endogenous metabolic pathways, thereby providing simultaneous measurement of biologic responses to environmental exposures. The present research examined quantification strategies to enhance the usefulness of HRM data for cumulative exposome research. The results provide a simple reference standardization protocol in which individual chemical concentrations in unknown samples are estimated by comparison to a concurrently analyzed, pooled reference sample with known chemical concentrations. The approach was tested using blinded analyses of amino acids in human samples and was found to be comparable to independent laboratory results based on surrogate standardization or internal standardization. Quantification was reproducible over a 13-month period and extrapolated to thousands of chemicals. The results show that reference standardization protocol provides an effective strategy that will enhance data collection for cumulative exposome research. In principle, the approach can be extended to other types of mass spectrometry and other analytical methods.

Novel metabolic markers for the risk of diabetes development in American Indians

OBJECTIVE To identify novel metabolic markers for diabetes development in American Indians. RESEARCH DESIGN AND METHODS Using an untargeted high-resolution liquid chromatography–mass spectrometry, we conducted metabolomics analysis of study participants who developed incident diabetes (n = 133) and those who did not (n = 298) from 2,117 normoglycemic American Indians followed for an average of 5.5 years in the Strong Heart Family Study. Relative abundances of metabolites were quantified in baseline fasting plasma of all 431 participants. Prospective association of each metabolite with risk of developing type 2 diabetes (T2D) was examined using logistic regression adjusting for established diabetes risk factors. RESULTS Seven metabolites (five known and two unknown) significantly predict the risk of T2D. Notably, one metabolite matching 2-hydroxybiphenyl was significantly associated with an increased risk of diabetes, whereas four metabolites matching PC (22:6/20:4), (3S)-7-hydroxy-2′,3′,4′,5′,8-pentamethoxyisoflavan, or tetrapeptides were significantly associated with decreased risk of diabetes. A multimarker score comprising all seven metabolites significantly improved risk prediction beyond established diabetes risk factors including BMI, fasting glucose, and insulin resistance. CONCLUSIONS The findings suggest that these newly detected metabolites may represent novel prognostic markers of T2D in American Indians, a group suffering from a disproportionately high rate of T2D.

The effects of age and dietary restriction on the tissue‐specific metabolome of Drosophila

Dietary restriction (DR) is a robust intervention that extends lifespan and slows the onset of age‐related diseases in diverse organisms. While significant progress has been made in attempts to uncover the genetic mechanisms of DR, there are few studies on the effects of DR on the metabolome. In recent years, metabolomic profiling has emerged as a powerful technology to understand the molecular causes and consequences of natural aging and disease‐associated phenotypes. Here, we use high‐resolution mass spectroscopy and novel computational approaches to examine changes in the metabolome from the head, thorax, abdomen, and whole body at multiple ages in Drosophila fed either a nutrient‐rich ad libitum (AL) or nutrient‐restricted (DR) diet. Multivariate analysis clearly separates the metabolome by diet in different tissues and different ages. DR significantly altered the metabolome and, in particular, slowed age‐related changes in the metabolome. Interestingly, we observed interacting metabolites whose correlation coefficients, but not mean levels, differed significantly between AL and DR. The number and magnitude of positively correlated metabolites was greater under a DR diet. Furthermore, there was a decrease in positive metabolite correlations as flies aged on an AL diet. Conversely, DR enhanced these correlations with age. Metabolic set enrichment analysis identified several known (e.g., amino acid and NAD metabolism) and novel metabolic pathways that may affect how DR effects aging. Our results suggest that network structure of metabolites is altered upon DR and may play an important role in preventing the decline of homeostasis with age.

Bile Acid Aspiration Associated With Lung Chemical Profile Linked to Other Biomarkers of Injury After Lung Transplantation

Aspiration of gastrointestinal contents has been linked to worse outcomes following lung transplantation but uncertainty exists about underlying mechanisms. We applied high‐resolution metabolomics of bronchoalveolar lavage fluid (BALF) in patients with episodic aspiration (defined by bile acids in the BALF) to identify potential metabolic changes associated with aspiration. Paired samples, one with bile acids and another without, from 29 stable lung transplant patients were studied. Liquid chromatography coupled to high‐resolution mass spectroscopy was used to interrogate metabolomic contents of these samples. Data were obtained for 7068 ions representing intermediary metabolites, environmental agents and chemicals associated with microbial colonization. A substantial number (2302) differed between bile acid positive and negative samples when analyzed by false discovery rate at q = 0.01. These included pathways associated with microbial metabolism. Hierarchical cluster analysis defined clusters of chemicals associated with bile acid aspiration that were correlated to previously reported biomarkers of lung injury including T cell granzyme B level and the chemoattractants CXCL9 and CXCL10. These data specifically link bile acids presence in lung allografts to inflammatory pathways known to segregate with worsening allograft outcome, and provide additional mechanistic insight into the association between reflux and lung allograft injury.

Transcriptome–metabolome wide association study (TMWAS) of maneb and paraquat neurotoxicity reveals network level interactions in toxicologic mechanism

A combination of the herbicide paraquat (PQ) and fungicide maneb (MB) has been linked to Parkinsons disease. Previous studies show that this involves an additive toxicity with at least two different mechanisms. However, detailed understanding of mixtures is often difficult to elucidate because of the multiple ways by which toxic agents can interact. In the present study, we used a combination of transcriptomics and metabolomics to investigate mechanisms of toxicity of PQ and MB in a neuroblastoma cell line. Conditions were studied with concentrations of PQ and MB that each individually caused 20% cell death and together caused 50% cell death. Transcriptomic and metabolomic samples were collected at time points prior to significant cell death. Statistical and bioinformatic methods were applied to the resulting 30,869 transcripts and 1358 metabolites. Results showed that MB significantly changed more transcripts and metabolites than PQ, and combined PQ + MB impacted more than MB alone. Transcriptome–metabolome-wide association study (TMWAS) showed that significantly changed transcripts and metabolites mapped to two network substructures, one associating with significant effects of MB and the other included features significantly associated with PQ + MB. The latter contained 4 clusters of genes and associated metabolites, with one containing genes for two cation transporters and a cation transporter regulatory protein also recognized as a pro-apoptotic protein. Other clusters included stress response genes and transporters linked to cytoprotective mechanisms. MB also had a significant network structure linked to cell proliferation. Together, the results show that the toxicologic mechanism of the combined neurotoxicity of PQ and MB involves network level interactions and that TMWAS provides an effective approach to investigate such complex mechanisms.

Mitochondrial metabolomics using high-resolution Fourier-transform mass spectrometry.

High-resolution Fourier-transform mass spectrometry (FTMS) provides important advantages in studies of metabolism because more than half of common intermediary metabolites can be measured in 10 min with minimal pre-detector separation and without ion dissociation. This capability allows unprecedented opportunity to study complex metabolic systems, such as mitochondria. Analysis of mouse liver mitochondria using FTMS with liquid chromatography shows that sex and genotypic differences in mitochondrial metabolism can be readily distinguished. Additionally, differences in mitochondrial function are readily measured, and many of the mitochondria-related metabolites are also measurable in plasma. Thus, application of high-resolution mass spectrometry provides an approach for integrated studies of complex metabolic processes of mitochondrial function and dysfunction in disease.

Metabolome-Wide Association Study of Primary Open Angle Glaucoma.

PURPOSE To determine if primary open-angle glaucoma (POAG) patients can be differentiated from controls based on metabolic characteristics. METHODS We used ultra-high resolution mass spectrometry with C18 liquid chromatography for metabolomic analysis on frozen plasma samples from 72 POAG patients and 72 controls. Metabolome-wide Spearman correlation was performed to select differentially expressed metabolites (DEM) correlated with POAG. We corrected P values for multiple testing using Benjamini and Hochberg false discovery rate (FDR). Hierarchical cluster analysis (HCA) was used to depict the relationship between participants and DEM. Differentially expressed metabolites were matched to the METLIN metabolomics database; both DEM and metabolites significantly correlating with DEM were analyzed using MetaboAnalyst to identify metabolic pathways altered in POAG. RESULTS Of the 2440 m/z (mass/charge) features recovered after filtering, 41 differed between POAG cases and controls at FDR = 0.05. Hierarchical cluster analysis revealed these DEM to associate into eight clusters; three of these clusters contained the majority of the DEM and included palmitoylcarnitine, hydroxyergocalciferol, and high-resolution METLIN matches to sphingolipids, other vitamin D-related metabolites, and terpenes. MetaboAnalyst also indicated likely alteration in steroid biosynthesis pathways. CONCLUSIONS Global ultrahigh resolution metabolomics emphasized the importance of altered lipid metabolism in POAG. The results suggest specific metabolic processes, such as those involving palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors, may contribute to POAG status and merit more detailed study with targeted methods.

A longitudinal analysis of the effects of age on the blood plasma metabolome in the common marmoset, Callithrix jacchus

Primates tend to be long-lived for their size with humans being the longest lived of all primates. There are compelling reasons to understand the underlying age-related processes that shape human lifespan. But the very fact of our long lifespan that makes it so compelling, also makes it especially difficult to study. Thus, in studies of aging, researchers have turned to non-human primate models, including chimpanzees, baboons, and rhesus macaques. More recently, the common marmoset, Callithrix jacchus, has been recognized as a particularly valuable model in studies of aging, given its small size, ease of housing in captivity, and relatively short lifespan. However, little is known about the physiological changes that occur as marmosets age. To begin to fill in this gap, we utilized high sensitivity metabolomics to define the longitudinal biochemical changes associated with age in the common marmoset. We measured 2104 metabolites from blood plasma at three separate time points over a 17-month period, and we completed both a cross-sectional and longitudinal analysis of the metabolome. We discovered hundreds of metabolites associated with age and body weight in both male and female animals. Our longitudinal analysis identified age-associated metabolic pathways that were not found in our cross-sectional analysis. Pathways enriched for age-associated metabolites included tryptophan, nucleotide, and xenobiotic metabolism, suggesting these biochemical pathways might play an important role in the basic mechanisms of aging in primates. Moreover, we found that many metabolic pathways associated with age were sex specific. Our work illustrates the power of longitudinal approaches, even in a short time frame, to discover novel biochemical changes that occur with age.