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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.

Late-onset Alzheimer’s disease (AD) can, in part, be considered a metabolic disease. Besides age, female sex and APOE ε4 genotype represent strong risk factors for AD that also give rise to large metabolic differences. We systematically investigated group-specific metabolic alterations by conducting stratified association analyses of 139 serum metabolites in 1,517 individuals from the AD Neuroimaging Initiative with AD biomarkers. We observed substantial sex differences in effects of 15 metabolites with partially overlapping differences for APOE ε4 status groups. Several group-specific metabolic alterations were not observed in unstratified analyses using sex and APOE ε4 as covariates. Combined stratification revealed further subgroup-specific metabolic effects limited to APOE ε4+ females. The observed metabolic alterations suggest that females experience greater impairment of mitochondrial energy production than males. Dissecting metabolic heterogeneity in AD pathogenesis can therefore enable grading the biomedical relevance for specific pathways within specific subgroups, guiding the way to personalized medicine., Sex and the APOE ε4 genotype are important risk factors for late-onset Alzheimer’s disease. In the current study, the authors investigate how sex and APOE ε4 genotype modify the association between Alzheimer’s disease biomarkers and metabolites in serum.

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines—including arginine, proline, and methionine sulfoxide—were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17 ≤ 7) and those who gained no meaningful benefits (17). Remitters exhibited (a) higher baseline levels of C3, C5, alpha-aminoadipic acid, sarcosine, and serotonin; and (b) higher week-8 levels of PC aa C34:1, PC aa C34:2, PC aa C36:2, and PC aa C36:4. These findings suggest that mitochondrial energetics—including acylcarnitine metabolism, transport, and its link to β-oxidation—and lipid membrane remodeling may play roles in SSRI treatment response.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

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

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., Measurement(s)bile acid • MedicationTechnology Type(s)ultra high performance liquid chromatography with mass spectrometer • Resource InformaticsFactor Type(s)age • biological sex • cognitive stateSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9724652

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.

Sexually transmitted disease (STD) partner services (PS) are a core component of STD programs. Data on costs are needed to support PS programming.In Washington State STD PS programs, disease intervention specialists (DIS) conduct telephone-based interviews and occasional field visits, offer expedited partner therapy to heterosexuals with gonorrhea or chlamydia, and promote human immunodeficiency virus (HIV) testing, preexposure prophylaxis, and HIV care. We conducted activity-based microcosting of PS, including: observational and self-reported time studies and interviews. We analyzed cost, surveillance, and service delivery data to determine costs per program outcomes.In King, Pierce, and Spokane counties, respectively, DIS allocated 6.5, 6.4, and 28.8 hours per syphilis case and 1.5, 1.6, and 2.9 hours per gonorrhea/chlamydia case, on average. In 2016, each full-time DIS investigated 270, 268, and 61 syphilis and 1177, 1105, and 769 gonorrhea/chlamydia cases. Greater than 80% of syphilis cases in King and Pierce were among men who have sex with men versus 38% in Spokane. Disease intervention specialists spent 12% to 39% of their time actively interviewing cases and notifying partners (clients), and the remaining time locating clients, coordinating and verifying care, and managing case reports. Time spent on expedited partner therapy, HIV testing, and referrals to HIV treatment or preexposure prophylaxis, was minimal (5 minutes per interview) at locations with resources outside PS staff. Program cost-per-interview ranged from US $527 to US $2210 for syphilis, US $219 to US $484 for gonorrhea, and US $164 to US $547 for chlamydia.The STD PS resource needs depended on epidemic characteristics and program models. Integrating HIV prevention objectives minimally impacted PS-specific program costs. Results can inform program planning, future budget impact, and cost-effectiveness analyses.

BackgroundAcylcarnitines have important functions in mitochondrial energetics and β-oxidation, and have been implicated to play a significant role in metabolic functions of the brain. This retrospective study examined whether plasma acylcarnitine profiles can help biochemically distinguish the three phenotypic subtypes of major depressive disorder (MDD)—(core depression (CD+), anxious depression (ANX+), and neurovegetative symptoms of melancholia (NVSM+))—following treatment with a selective serotonin reuptake inhibitor (SSRI).MethodsDepressed outpatients (n=240) from the Mayo Clinic Pharmacogenomics Research Network were treated with citalopram or escitalopram for eight weeks. Plasma samples collected at baseline and eight weeks post-treatment were profiled for multiple-, short-, medium- and long-chain acylcarnitine levels using AbsoluteIDQ®p180-Kit and LC-MS. Linear mixed effects models were used to examine whether acylcarnitine levels discriminate the clinical phenotypes at baseline or eight weeks post-treatment, and whether temporal changes in acylcarnitine profiles differ between groups.ResultsAt baseline, significantly lower concentrations of short- and long-chain acylcarnitines were found in CD+ and NVSM+ compared to ANX+, and the short-chain acylcarnitines remained lower after eight weeks. At eight weeks, the medium- and long-chain acylcarnitines were significantly lower in NVSM+ compared to ANX+. Regarding changes baseline to week eight, short-chain acylcarnitine levels significantly increased in CD+ and ANX+, and medium- and long-chain acylcarnitines significantly decreased in NVSM+ and CD+.ConclusionsIn depressed patients treated with SSRIs, β-oxidation and mitochondrial energetics as evaluated by levels and changes in acylcarnitines may provide the biochemical basis of the clinical heterogeneity of MDD, especially when combined with clinical characteristics.

IntroductionIncreasing evidence suggests a role for the gut microbiome in central nervous system disorders and specific role for the gut-brain axis in neurodegeneration. Bile acids (BA), 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 disease (AD).MethodsSerum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1,464 subjects including 370 cognitively normal older adults (CN), 284 with early mild cognitive impairment (MCI), 505 with late MCI, 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 cofounders and multiple testing.ResultsIn AD compared to CN, we observed significantly lower serum concentrations of a primary BA (cholic acid CA) and increased levels of the bacterially produced, secondary BA, deoxycholic acid (DCA), and its glycine and taurine conjugated forms. An increased ratio of DCA: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.ConclusionWe 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.

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.

IntroductionThe Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance.MethodsFasting serum samples from the Alzheimer's Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted.Results Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and α-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for Aβ1–42, tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease.DiscussionMetabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery.

The effects of integrative medicine practices such as meditation and Ayurveda on human physiology are not fully understood. The aim of this study was to identify altered metabolomic profiles following an Ayurveda-based intervention. In the experimental group, 65 healthy male and female subjects participated in a 6-day Panchakarma-based Ayurvedic intervention which included herbs, vegetarian diet, meditation, yoga, and massage. A set of 12 plasma phosphatidylcholines decreased (adjusted p Panchakarma-induced modulation of metabotypes. Panchakarma promoted statistically significant changes in plasma levels of phosphatidylcholines, sphingomyelins and others in just 6 days. Forthcoming studies that integrate metabolomics with genomic, microbiome and physiological parameters may facilitate a broader systems-level understanding and mechanistic insights into these integrative practices that are employed to promote health and well-being.

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.

Liquid chromatography (LC) combined with atmospheric pressure chemical ionization mass spectrometry was used to identify phase I and II metabolites of the drug BW 1370U87 in dog and human urine. Additional analysis of individual high-performance liquid chromatograph fractions collected from dog urine by combined gas chromatography/mass spectrometry identified one metabolite which was not detected by LC/MS methods. Using negative-ion LC/MS, the majority of BW 1370U87 metabolites in human urine were identified as glucuronic acid conjugates of phase I oxidative metabolites. The negative-ion fragmentation produced by low-energy collisionally activated decomposition (CAD), studied by tandem mass spectrometry experiments, confirmed that these compounds were drug-related and allowed metabolite structures to be assigned. Product-ion spectra of the metabolites were dominated by the loss of neutral molecules from even-electron deprotonated [M − H]− ions.

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.