Metabolomic Signature as a Predictor of Liver Disease Events in Patients With HIV/HCV Coinfection.

BACKGROUND: Advanced liver disease due to hepatitis C virus (HCV) is a leading cause of human immunodeficiency virus (HIV)-related morbidity and mortality. There remains a need to develop noninvasive predictors of clinical outcomes in persons with HIV/HCV coinfection. METHODS: We conducted a nested case-control study in 126 patients with HIV/HCV and utilized multiple quantitative metabolomic assays to identify a prognostic profile that predicts end-stage liver disease (ESLD) events including ascites, hepatic encephalopathy, hepatocellular carcinoma, esophageal variceal bleed, and spontaneous bacterial peritonitis. Each analyte class was included in predictive modeling, and area under the receiver operator characteristic curves (AUC) and accuracy were determined. RESULTS: The baseline model including demographic and clinical data had an AUC of 0.79. Three models (baseline plus amino acids, lipid metabolites, or all combined metabolites) had very good accuracy (AUC, 0.84-0.89) in differentiating patients at risk of developing an ESLD complication up to 2 years in advance. The all combined metabolites model had sensitivity 0.70, specificity 0.85, positive likelihood ratio 4.78, and negative likelihood ratio 0.35. CONCLUSIONS: We report that quantification of a novel set of metabolites may allow earlier identification of patients with HIV/HCV who have the greatest risk of developing ESLD clinical events.

Alzheimer's Risk Factors Age, APOE Genotype, and Sex Drive Distinct Molecular Pathways.

Evidence suggests interplay among the three major risk factors for Alzheimer's disease (AD): age, APOE genotype, and sex. Here, we present comprehensive datasets and analyses of brain transcriptomes and blood metabolomes from human apoE2-, apoE3-, and apoE4-targeted replacement mice across young, middle, and old ages with both sexes. We found that age had the greatest impact on brain transcriptomes highlighted by an immune module led by Trem2 and Tyrobp, whereas APOE4 was associated with upregulation of multiple Serpina3 genes. Importantly, these networks and gene expression changes were mostly conserved in human brains. Finally, we observed a significant interaction between age, APOE genotype, and sex on unfolded protein response pathway. In the periphery, APOE2 drove distinct blood metabolome profile highlighted by the upregulation of lipid metabolites. Our work identifies unique and interactive molecular pathways underlying AD risk factors providing valuable resources for discovery and validation research in model systems and humans.

Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics.

Vendor-independent software tools for quantification of small molecules and metabolites are lacking, especially for targeted analysis workflows. Skyline is a freely available, open-source software tool for targeted quantitative mass spectrometry method development and data processing with a 10 year history supporting six major instrument vendors. Designed initially for proteomics analysis, we describe the expansion of Skyline to data for small molecule analysis, including selected reaction monitoring, high-resolution mass spectrometry, and calibrated quantification. This fundamental expansion of Skyline from a peptide-sequence-centric tool to a molecule-centric tool makes it agnostic to the source of the molecule while retaining Skyline features critical for workflows in both peptide and more general biomolecular research. The data visualization and interrogation features already available in Skyline, such as peak picking, chromatographic alignment, and transition selection, have been adapted to support small molecule data, including metabolomics. Herein, we explain the conceptual workflow for small molecule analysis using Skyline, demonstrate Skyline performance benchmarked against a comparable instrument vendor software tool, and present additional real-world applications. Further, we include step-by-step instructions on using Skyline for small molecule quantitative method development and data analysis on data acquired with a variety of mass spectrometers from multiple instrument vendors.

International Ring Trial of a High Resolution Targeted Metabolomics and Lipidomics Platform for Serum and Plasma Analysis.

A challenge facing metabolomics in the analysis of large human cohorts is the cross-laboratory comparability of quantitative metabolomics measurements. In this study, 14 laboratories analyzed various blood specimens using a common experimental protocol provided with the Biocrates AbsoluteIDQ p400HR kit, to quantify up to 408 metabolites. The specimens included human plasma and serum from male and female donors, mouse and rat plasma, as well as NIST SRM 1950 reference plasma. The metabolite classes covered range from polar (e.g., amino acids and biogenic amines) to nonpolar (e.g., diacyl- and triacyl-glycerols), and they span 11 common metabolite classes. The manuscript describes a strict system suitability testing (SST) criteria used to evaluate each laboratory's readiness to perform the assay, and provides the SST Skyline documents for public dissemination. The study found approximately 250 metabolites were routinely quantified in the sample types tested, using Orbitrap instruments. Interlaboratory variance for the NIST SRM-1950 has a median of 10% for amino acids, 24% for biogenic amines, 38% for acylcarnitines, 25% for glycerolipids, 23% for glycerophospholipids, 16% for cholesteryl esters, 15% for sphingolipids, and 9% for hexoses. Comparing to consensus values for NIST SRM-1950, nearly 80% of comparable analytes demonstrated bias of <50% from the reference value. The findings of this study result in recommendations of best practices for system suitability, quality control, and calibration. We demonstrate that with appropriate controls, high-resolution metabolomics can provide accurate results with good precision across laboratories, and the p400HR therefore is a reliable approach for generating consistent and comparable metabolomics data.

Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts.

Alzheimer's disease (AD) is the most common cause of dementia. The mechanism of disease development and progression is not well understood, but increasing evidence suggests multifactorial etiology, with a number of genetic, environmental, and aging-related factors. There is a growing body of evidence that metabolic defects may contribute to this complex disease. To interrogate the relationship between system level metabolites and disease susceptibility and progression, the AD Metabolomics Consortium (ADMC) in partnership with AD Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for patients in the ADNI1 cohort. We used the Biocrates Bile Acids platform to evaluate the association of metabolic levels with disease risk and progression. We detail the quantitative metabolomics data generated on the baseline samples from ADNI1 and ADNIGO/2 (370 cognitively normal, 887 mild cognitive impairment, and 305 AD). Similar to our previous reports on ADNI1, we present the tools for data quality control and initial analysis. This data descriptor represents the third in a series of comprehensive metabolomics datasets from the ADMC on the ADNI.

Altered bile acid profile associates with cognitive impairment in Alzheimer's disease-An emerging role for gut microbiome.

INTRODUCTION: Increasing evidence suggests a role for the gut microbiome in central nervous system disorders and a specific role for the gut-brain axis in neurodegeneration. Bile acids (BAs), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer's disease (AD). METHODS: Serum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1464 subjects including 370 cognitively normal older adults, 284 with early mild cognitive impairment, 505 with late mild cognitive impairment, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD-related genetic variants, adjusting for confounders and multiple testing. RESULTS: In AD compared to cognitively normal older adults, we observed significantly lower serum concentrations of a primary BA (cholic acid [CA]) and increased levels of the bacterially produced, secondary BA, deoxycholic acid, and its glycine and taurine conjugated forms. An increased ratio of deoxycholic acid:CA, which reflects 7α-dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response-related genes implicated in AD showed associations with BA profiles. DISCUSSION: We report for the first time an association between altered BA profile, genetic variants implicated in AD, and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut-liver-brain axis in the pathogenesis of AD.

Targeted metabolomics and medication classification data from participants in the ADNI1 cohort.

Alzheimer's disease (AD) is the most common neurodegenerative disease presenting major health and economic challenges that continue to grow. Mechanisms of disease are poorly understood but significant data point to metabolic defects that might contribute to disease pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Alzheimer Disease Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for AD. Using targeted and non- targeted metabolomics and lipidomics platforms we are mapping metabolic pathway and network failures across the trajectory of disease. In this report we present quantitative metabolomics data generated on serum from 199 control, 356 mild cognitive impairment and 175 AD subjects enrolled in ADNI1 using AbsoluteIDQ-p180 platform, along with the pipeline for data preprocessing and medication classification for confound correction. The dataset presented here is the first of eight metabolomics datasets being generated for broad biochemical investigation of the AD metabolome. We expect that these collective metabolomics datasets will provide valuable resources for researchers to identify novel molecular mechanisms contributing to AD pathogenesis and disease phenotypes.

Comprehensive Proteomic and Metabolomic Signatures of Nontypeable Haemophilus influenzae-Induced Acute Otitis Media Reveal Bacterial Aerobic Respiration in an Immunosuppressed Environment.

A thorough understanding of the molecular details of the interactions between bacteria and host are critical to ultimately prevent disease. Recent technological advances allow simultaneous analysis of host and bacterial protein and metabolic profiles from a single small tissue sample to provide insight into pathogenesis. We used the chinchilla model of human otitis media to determine, for the first time, the most expansive delineation of global changes in protein and metabolite profiles during an experimentally induced disease. After 48 h of infection with nontypeable Haemophilus influenzae, middle ear tissue lysates were analyzed by high-resolution quantitative two-dimensional liquid chromatography-tandem mass spectrometry. Dynamic changes in 105 chinchilla proteins and 66 metabolites define the early proteomic and metabolomic signature of otitis media. Our studies indicate that establishment of disease coincides with actin morphogenesis, suppression of inflammatory mediators, and bacterial aerobic respiration. We validated the observed increase in the actin-remodeling complex, Arp2/3, and experimentally showed a role for Arp2/3 in nontypeable Haemophilus influenzae invasion. Direct inhibition of actin branch morphology altered bacterial invasion into host epithelial cells, and is supportive of our efforts to use the information gathered to modify outcomes of disease. The twenty-eight nontypeable Haemophilus influenzae proteins identified participate in carbohydrate and amino acid metabolism, redox homeostasis, and include cell wall-associated metabolic proteins. Quantitative characterization of the molecular signatures of infection will redefine our understanding of host response driven developmental changes during pathogenesis. These data represent the first comprehensive study of host protein and metabolite profiles in vivo in response to infection and show the feasibility of extensive characterization of host protein profiles during disease. Identification of novel protein targets and metabolic biomarkers will advance development of therapeutic and diagnostic options for treatment of disease.

Inter-Laboratory Robustness of Next-Generation Bile Acid Study in Mice and Humans: International Ring Trial Involving 12 Laboratories.

BACKGROUND: The increasing relevance of individual bile acids quantification in biological samples requires analytical standardization to guarantee robustness and reliability of laboratory results. We have organized the first international ring trial, carried out in 12 laboratories, to evaluate the newly developed LC-MS/MS-based test kit for bile acid analysis. METHODS: Each laboratory received a Biocrates® Bile Acids Kit including system suitability test (SST) protocol. The kit is designed to analyze 16 individual human and 19 mouse bile acids. A set of 9 human and mouse plasma samples was measured in replicates. Laboratories were first required to pass the acceptance criteria for the SST. Within the subset of laboratories passing SST criteria, we evaluated how many laboratories met the target criteria of 80% of reported values with a relative accuracy within the 70%-130% range and analytical precisions (%CV) below 30%. RESULTS: A total of 12 of 16 participating laboratories passed the SST as the prerequisite to enter the ring trial. All 12 laboratories were then able to successfully run the kit and ring trial samples. Of the overall reported values, 94% were within 70%-130% relative accuracy range. Mean precision was 8.3% CV. The condition of CV <30% was fulfilled by 99% of the reported values. CONCLUSIONS: The first publically available interlaboratory ring trial for standardized bile acids quantification in human and mouse plasma samples showed very good analytical performance, within acceptance criteria typically applied in the preclinical environment. The kit is therefore suitable for standardized quantitative bile acid analysis and the establishment of reference values.

Optimizing Urine Processing Protocols for Protein and Metabolite Detection.

BACKGROUND: In urine, factors such as timing of voids, and duration at room temperature (RT) may affect the quality of recovered protein and metabolite data. Additives may aid with detection, but can add more complexity in sample collection or analysis. We aimed to identify the optimal urine processing protocol for clinically-obtained urine samples that allows for the highest protein and metabolite yields with minimal degradation. METHODS: Healthy women provided multiple urine samples during the same day. Women collected their first morning (1st AM) void and another "random void". Random voids were aliquotted with: 1) no additive; 2) boric acid (BA); 3) protease inhibitor (PI); or 4) both BA + PI. Of these aliquots, some were immediately stored at 4°C, and some were left at RT for 4 hours. Proteins and individual metabolites were quantified, normalized to creatinine concentrations, and compared across processing conditions. Sample pools corresponding to each processing condition were analyzed using mass spectrometry to assess protein degradation. RESULTS: Ten Caucasian women between 35-65 years of age provided paired 1st morning and random voided urine samples. Normalized protein concentrations were slightly higher in 1st AM compared to random "spot" voids. The addition of BA did not significantly change proteins, while PI significantly improved normalized protein concentrations, regardless of whether samples were immediately cooled or left at RT for 4 hours. In pooled samples, there were minimal differences in protein degradation under the various conditions we tested. In metabolite analyses, there were significant differences in individual amino acids based on the timing of the void. CONCLUSIONS: For comparative translational research using urine, information about void timing should be collected and standardized. For urine samples processed in the same day, BA does not appear to be necessary while the addition of PI enhances protein yields, regardless of 4°C or RT storage temperature.

Biopharmaceutics classification system: validation and learnings of an in vitro permeability assay.

The Biopharmaceutics Classification System (BCS) is the scientific basis for classifying drugs based on their aqueous solubility and intestinal permeability that supports in vivo bioavailability and bioequivalence waivers for immediate-release solid dosage form drugs. One requirement of the BCS is that the permeability method must be validated. In order to accommodate the variety of in vitro/in situ permeability models, the BCS Guidance gives a general framework for the validation requirements, necessitating implemented experimental details to be selected by the applicant laboratory. The objective of this work was to define the parameters for a cell based in vitro permeability method (e.g., cell type, pH, transport direction, time, and concentration) and validate the method to support formal BCS classification of drugs. Twenty reference drugs were selected and permeability values determined using the Madin-Darby canine kidney type II cell line heterologously expressing the human P-glycoprotein transporter (MDCKII-MDR1). A rank order relationship was established between the in vitro permeability value and human intestinal absorption values. This relationship was as predicted and validates the MDCKII-MDR1 permeability method as defined by the BCS Guidance. The final validated in vitro permeability method employs the MDCKII-MDR1 cell line incubated with the Pgp inhibitor GF120918. It is a unidirectional apical-to-basolateral transport assay performed at apical pH values of 5.5 and 7.4 and a basolateral pH of 7.4. Four reference standards (metoprolol, pindolol, labetalol and ranitidine) dosed and analyzed as a single cassette are included in each experiment. A strategy on selection of drug concentrations and on how to deal with problematic compounds (i.e., those suffering from poor mass balance) is discussed.

An in vitro mechanistic study to elucidate the desipramine/bupropion clinical drug-drug interaction.

There are documented clinical drug-drug interactions between bupropion and the CYP2D6-metabolized drug desipramine resulting in marked (5-fold) increases in desipramine exposure. This finding was unexpected as CYP2D6 does not play a significant role in bupropion clearance, and bupropion and its major active metabolite, hydroxybupropion, are not strong CYP2D6 inhibitors in vitro. The aims of this study were to investigate whether bupropion's reductive metabolites, threohydrobupropion and erythrohydrobupropion, contribute to the drug interaction with desipramine. In human liver microsomes using the CYP2D6 probe substrate bufuralol, erythrohydrobupropion and threohydrobupropion were more potent inhibitors of CYP2D6 activity (K(i) = 1.7 and 5.4 microM, respectively) than hydroxybupropion (K(i) = 13 microM) or bupropion (K(i) = 21 microM). Furthermore, neither bupropion nor its metabolites were metabolism-dependent CYP2D6 inhibitors. Using the in vitro kinetic constants and estimated liver concentrations of bupropion and its metabolites, modeling was able to predict within 2-fold the increase in desipramine exposure observed when coadministered with bupropion. This work indicates that the reductive metabolites of bupropion are potent competitive CYP2D6 inhibitors in vivo and provides a mechanistic explanation for the clinical drug-drug interaction between bupropion and desipramine.

Enzymology of a carbonyl reduction clearance pathway for the HIV integrase inhibitor, S-1360: role of human liver cytosolic aldo-keto reductases.

S-1360, a 1,3-diketone derivative, was the first HIV integrase inhibitor to enter human trials. Clinical data suggested involvement of non-cytochrome P450 clearance pathways, including reduction and glucuronidation. Reduction of S-1360 generates a key metabolite in humans, designated HP1, and constitutes a major clearance pathway. For characterization of subcellular location and cofactor dependence of HP1 formation, [(14)C]-S-1360 was incubated with commercially available pooled human liver fractions, including microsomes, cytosol, and mitochondria, followed by HPLC analysis with radiochemical detection. Incubations were performed in the presence and absence of the cofactors NADH or NADPH. Results showed that the enzyme system responsible for generation of HP1 in vitro is cytosolic and NADPH-dependent, implicating aldo-keto reductases (AKRs) and/or short-chain dehydrogenases/reductases (SDRs). A validated LC/MS/MS method was developed for investigating the reduction of S-1360 in detail. The reduction reaction exhibited sigmoidal kinetics with a K(m,app) of 2 microM and a Hill coefficient of 2. The ratio of V(max)/K(m) was approximately 1 ml/(min mg cytosolic protein). The S-1360 kinetic data were consistent with positive cooperativity and a single enzyme system. The relative contributions of AKRs and SDRs were examined through the use of chemical inhibitors. For these experiments, non-radiolabeled S-1360 was incubated with pooled human liver cytosol and NADPH in the presence of inhibitors, followed by quantitation of HP1 by LC/MS/MS. Quercetin and menadione produced approximately 30% inhibition at a concentration of 100 microM. Enzymes sensitive to these inhibitors include the carbonyl reductases (CRs), a subset of the SDR enzyme family predominantly located in the cytosol. Flufenamic acid and phenolphthalein were the most potent inhibitors, with > 67% inhibition at a concentration of 20 microM, implicating the AKR enzyme family. The cofactor dependence, subcellular location, and chemical inhibitor results implicated the aldo-keto reductase family of enzymes as the most likely pathway for generation of the major metabolite HP1 from S-1360.