The HuMet Repository: Watching human metabolism at work.

The human metabolism constantly responds to stimuli such as food intake, fasting, exercise, and stress, triggering adaptive biochemical processes across multiple metabolic pathways. To understand the role of these processes and disruptions thereof in health and disease, detailed documentation of healthy metabolic responses is needed but still scarce on a time-resolved metabolome-wide level. Here, we present the HuMet Repository, a web-based resource for exploring dynamic metabolic responses to six physiological challenges (exercise, 36 h fasting, oral glucose and lipid loads, mixed meal, cold stress) in healthy subjects. For building this resource, we integrated existing and newly derived metabolomics data measured in blood, urine, and breath samples of 15 young healthy men at up to 56 time points during the six highly standardized challenge tests conducted over four days. The data comprise 1.1 million data points acquired on multiple platforms with temporal profiles of 2,656 metabolites from a broad range of biochemical pathways. By embedding the dataset into an interactive web application, we enable users to easily access, search, filter, analyze, and visualize the time-resolved metabolomic readouts and derived results. Users can put metabolites into their larger context by identifying metabolites with similar trajectories or by visualizing metabolites within holistic metabolic networks to pinpoint pathways of interest. In three showcases, we outline the value of the repository for gaining biological insights and generating hypotheses by analyzing the wash-out of dietary markers, the complementarity of metabolomics platforms in dynamic versus cross-sectional data, and similarities and differences in systemic metabolic responses across challenges. With its comprehensive collection of time-resolved metabolomics data, the HuMet Repository, freely accessible at https://humet.org/, is a reference for normal, healthy responses to metabolic challenges in young males. It will enable researchers with and without computational expertise, to flexibly query the data for their own research into the dynamics of human metabolism.

Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine.

The kidneys operate at the interface of plasma and urine by clearing molecular waste products while retaining valuable solutes. Genetic studies of paired plasma and urine metabolomes may identify underlying processes. We conducted genome-wide studies of 1,916 plasma and urine metabolites and detected 1,299 significant associations. Associations with 40% of implicated metabolites would have been missed by studying plasma alone. We detected urine-specific findings that provide information about metabolite reabsorption in the kidney, such as aquaporin (AQP)-7-mediated glycerol transport, and different metabolomic footprints of kidney-expressed proteins in plasma and urine that are consistent with their localization and function, including the transporters NaDC3 (SLC13A3) and ASBT (SLC10A2). Shared genetic determinants of 7,073 metabolite-disease combinations represent a resource to better understand metabolic diseases and revealed connections of dipeptidase 1 with circulating digestive enzymes and with hypertension. Extending genetic studies of the metabolome beyond plasma yields unique insights into processes at the interface of body compartments.

Metabolome Genome-Wide Association Study Identifies 74 Novel Genomic Regions Influencing Plasma Metabolites Levels.

Metabolites are small products of metabolism that provide a snapshot of the wellbeing of an organism and the mechanisms that control key physiological processes involved in health and disease. Here we report the results of a genome-wide association study of 722 circulating metabolite levels in 8809 subjects of European origin, providing both breadth and depth. These analyses identified 202 unique genomic regions whose variations are associated with the circulating levels of 478 different metabolites. Replication with a subset of 208 metabolites that were available in an independent dataset for a cohort of 1768 European subjects confirmed the robust associations, including 74 novel genomic regions not associated with any metabolites in previous works. This study enhances our knowledge of genetic mechanisms controlling human metabolism. Our findings have major potential for identifying novel targets and developing new therapeutic strategies.

Long-Chain Acylcholines Link Butyrylcholinesterase to Regulation of Non-neuronal Cholinergic Signaling.

Acylcholines are comprised of an acyl chain esterified to a choline moiety; acetylcholine is the best-characterized member of this class, functioning as a neurotransmitter in the central and peripheral nervous systems as well as an inhibitor of cytokine production by macrophages and other innate immune cells. Acylcholines are metabolized by a class of cholinesterases, including acetylcholinesterase (a specific regulator of acetylcholine levels) and butyrylcholinesterase (BChE, an enigmatic enzyme whose function has not been resolved by genetic knockout models). BChE provides reserve capacity to hydrolyze acetylcholine, but its importance is arguable given acetylcholinesterase is the most catalytically efficient enzyme characterized to date. While known to be substrates of BChE in vitro, endogenous production of long-chain acylcholines is a recent discovery enabled by untargeted metabolomics. Compared to acetylcholine, long-chain acylcholines show greater stability in circulation with homeostatic levels-dictated by synthesis and clearance-suggested to impact cholinergic receptor sensitivity of acetylcholine with varying levels of antagonism. Acylcholines then provide a link between BChE and non-neuronal acetylcholine signaling, filling a gap in understanding around how imbalances between acylcholines and BChE could modulate inflammatory disease, such as the "cytokine storm" identified in severe COVID-19. Areas for further research, development, and clinical testing are outlined.

Self-Reported Medication Use and Urinary Drug Metabolites in the German Chronic Kidney Disease (GCKD) Study.

BACKGROUND: Polypharmacy is common among patients with CKD, but little is known about the urinary excretion of many drugs and their metabolites among patients with CKD. METHODS: To evaluate self-reported medication use in relation to urine drug metabolite levels in a large cohort of patients with CKD, the German Chronic Kidney Disease study, we ascertained self-reported use of 158 substances and 41 medication groups, and coded active ingredients according to the Anatomical Therapeutic Chemical Classification System. We used a nontargeted mass spectrometry-based approach to quantify metabolites in urine; calculated specificity, sensitivity, and accuracy of medication use and corresponding metabolite measurements; and used multivariable regression models to evaluate associations and prescription patterns. RESULTS: Among 4885 participants, there were 108 medication-drug metabolite pairs on the basis of reported medication use and 78 drug metabolites. Accuracy was excellent for measurements of 36 individual substances in which the unchanged drug was measured in urine (median, 98.5%; range, 61.1%-100%). For 66 pairs of substances and their related drug metabolites, median measurement-based specificity and sensitivity were 99.2% (range, 84.0%-100%) and 71.7% (range, 1.2%-100%), respectively. Commonly prescribed medications for hypertension and cardiovascular risk reduction-including angiotensin II receptor blockers, calcium channel blockers, and metoprolol-showed high sensitivity and specificity. Although self-reported use of prescribed analgesics (acetaminophen, ibuprofen) was <3% each, drug metabolite levels indicated higher usage (acetaminophen, 10%-26%; ibuprofen, 10%-18%). CONCLUSIONS: This comprehensive screen of associations between urine drug metabolite levels and self-reported medication use supports the use of pharmacometabolomics to assess medication adherence and prescription patterns in persons with CKD, and indicates under-reported use of medications available over the counter, such as analgesics.

Urine Metabolite Levels, Adverse Kidney Outcomes, and Mortality in CKD Patients: A Metabolome-wide Association Study.

RATIONALE & OBJECTIVE: Mechanisms underlying the variable course of disease progression in patients with chronic kidney disease (CKD) are incompletely understood. The aim of this study was to identify novel biomarkers of adverse kidney outcomes and overall mortality, which may offer insights into pathophysiologic mechanisms. STUDY DESIGN: Metabolome-wide association study. SETTING & PARTICIPANTS: 5,087 patients with CKD enrolled in the observational German Chronic Kidney Disease Study. EXPOSURES: Measurements of 1,487 metabolites in urine. OUTCOMES: End points of interest were time to kidney failure (KF), a combined end point of KF and acute kidney injury (KF+AKI), and overall mortality. ANALYTICAL APPROACH: Statistical analysis was based on a discovery-replication design (ratio 2:1) and multivariable-adjusted Cox regression models. RESULTS: After a median follow-up of 4 years, 362 patients died, 241 experienced KF, and 382 experienced KF+AKI. Overall, we identified 55 urine metabolites whose levels were significantly associated with adverse kidney outcomes and/or mortality. Higher levels of C-glycosyltryptophan were consistently associated with all 3 main end points (hazard ratios of 1.43 [95% CI, 1.27-1.61] for KF, 1.40 [95% CI, 1.27-1.55] for KF+AKI, and 1.47 [95% CI, 1.33-1.63] for death). Metabolites belonging to the phosphatidylcholine pathway showed significant enrichment. Members of this pathway contributed to the improvement of the prediction performance for KF observed when multiple metabolites were added to the well-established Kidney Failure Risk Equation. LIMITATIONS: Findings among patients of European ancestry with CKD may not be generalizable to the general population. CONCLUSIONS: Our comprehensive screen of the association between urine metabolite levels and adverse kidney outcomes and mortality identifies metabolites that predict KF and represents a valuable resource for future studies of biomarkers of CKD progression.

Serum metabolites reflecting gut microbiome alpha diversity predict type 2 diabetes.

Type 2 diabetes (T2D) is associated with reduced gut microbiome diversity, although the cause is unclear. Metabolites generated by gut microbes also appear to be causative factors in T2D. We therefore searched for serum metabolites predictive of gut microbiome diversity in 1018 females from TwinsUK with concurrent metabolomic profiling and microbiome composition. We generated a Microbial Metabolites Diversity (MMD) score of six circulating metabolites that explained over 18% of the variance in microbiome alpha diversity. Moreover, the MMD score was associated with a significantly lower odds of prevalent (OR[95%CI] = 0.22[0.07;0.70], P = .01) and incident T2D (HR[95%CI] = 0.31[0.11,0.90], P = .03). We replicated our results in 1522 individuals from the ARIC study (prevalent T2D: OR[95%CI] = 0.79[0.64,0.96], P = .02, incident T2D: HR[95%CI] = 0.87[0.79,0.95], P = .003). The MMD score mediated 28%[15%,94%] of the total effect of gut microbiome on T2D after adjusting for confounders. Metabolites predicting higher microbiome diversity included 3-phenylpropionate(hydrocinnamate), indolepropionate, cinnamoylglycine and 5-alpha-pregnan-3beta,20 alpha-diol monosulfate(2) of which indolepropionate and phenylpropionate have already been linked to lower incidence of T2D. Metabolites correlating with lower microbial diversity included glutarate and imidazole propionate, of which the latter has been implicated in insulin resistance. Our results suggest that the effect of gut microbiome diversity on T2D is largely mediated by microbial metabolites, which might be modifiable by diet.

Urine 6-Bromotryptophan: Associations with Genetic Variants and Incident End-Stage Kidney Disease.

Higher serum 6-bromotryptophan has been associated with lower risk of chronic kidney disease (CKD) progression, implicating mechanisms beyond renal clearance. We studied genetic determinants of urine 6-bromotryptophan and its association with CKD risk factors and incident end-stage kidney disease (ESKD) in 4,843 participants of the German Chronic Kidney Disease (GCKD) study. 6-bromotryptophan was measured from urine samples using mass spectrometry. Patients with higher levels of urine 6-bromotryptophan had higher baseline estimated glomerular filtration rate (eGFR, p < 0.001). A genome-wide association study of urine 6-bromotryptophan identified two significant loci possibly related to its tubular reabsorption, SLC6A19, and its production, ERO1A, which was also associated with serum 6-bromotryptophan in an independent study. The association between urine 6-bromotryptophan and time to ESKD was assessed using Cox regression. There were 216 ESKD events after four years of follow-up. Compared with patients with undetectable levels, higher 6-bromotryptophan levels were associated with lower risk of ESKD in models unadjusted and adjusted for ESKD risk factors other than eGFR (

Genetic studies of urinary metabolites illuminate mechanisms of detoxification and excretion in humans.

The kidneys integrate information from continuous systemic processes related to the absorption, distribution, metabolism and excretion (ADME) of metabolites. To identify underlying molecular mechanisms, we performed genome-wide association studies of the urinary concentrations of 1,172 metabolites among 1,627 patients with reduced kidney function. The 240 unique metabolite-locus associations (metabolite quantitative trait loci, mQTLs) that were identified and replicated highlight novel candidate substrates for transport proteins. The identified genes are enriched in ADME-relevant tissues and cell types, and they reveal novel candidates for biotransformation and detoxification reactions. Fine mapping of mQTLs and integration with single-cell gene expression permitted the prioritization of causal genes, functional variants and target cell types. The combination of mQTLs with genetic and health information from 450,000 UK Biobank participants illuminated metabolic mediators, and hence, novel urinary biomarkers of disease risk. This comprehensive resource of genetic targets and their substrates is informative for ADME processes in humans and is relevant to basic science, clinical medicine and pharmaceutical research.

Genome-wide scan identifies novel genetic loci regulating salivary metabolite levels.

Saliva, as a biofluid, is inexpensive and non-invasive to obtain, and provides a vital tool to investigate oral health and its interaction with systemic health conditions. There is growing interest in salivary biomarkers for systemic diseases, notably cardiovascular disease. Whereas hundreds of genetic loci have been shown to be involved in the regulation of blood metabolites, leading to significant insights into the pathogenesis of complex human diseases, little is known about the impact of host genetics on salivary metabolites. Here we report the first genome-wide association study exploring 476 salivary metabolites in 1419 subjects from the TwinsUK cohort (discovery phase), followed by replication in the Study of Health in Pomerania (SHIP-2) cohort. A total of 14 distinct locus-metabolite associations were identified in the discovery phase, most of which were replicated in SHIP-2. While only a limited number of the loci that are known to regulate blood metabolites were also associated with salivary metabolites in our study, we identified several novel saliva-specific locus-metabolite associations, including associations for the AGMAT (with the metabolites 4-guanidinobutanoate and beta-guanidinopropanoate), ATP13A5 (with the metabolite creatinine) and DPYS (with the metabolites 3-ureidopropionate and 3-ureidoisobutyrate) loci. Our study suggests that there may be regulatory pathways of particular relevance to the salivary metabolome. In addition, some of our findings may have clinical significance, such as the utility of the pyrimidine (uracil) degradation metabolites in predicting 5-fluorouracil toxicity and the role of the agmatine pathway metabolites as biomarkers of oral health.

Interplay between the human gut microbiome and host metabolism.

The human gut is inhabited by a complex and metabolically active microbial ecosystem. While many studies focused on the effect of individual microbial taxa on human health, their overall metabolic potential has been under-explored. Using whole-metagenome shotgun sequencing data in 1,004 twins, we first observed that unrelated subjects share, on average, almost double the number of metabolic pathways (82%) than species (43%). Then, using 673 blood and 713 faecal metabolites, we found metabolic pathways to be associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species showed less than 3,000 associations. Finally, we estimated that the microbiome was involved in a dialogue between 71% of faecal, and 15% of blood, metabolites. This study underlines the importance of studying the microbial metabolic potential rather than focusing purely on taxonomy to find therapeutic and diagnostic targets, and provides a unique resource describing the interplay between the microbiome and the systemic and faecal metabolic environments.

Metabolomic profiling identifies novel associations with Electrolyte and Acid-Base Homeostatic patterns.

Electrolytes have a crucial role in maintaining health and their serum levels are homeostatically maintained within a narrow range by multiple pathways involving the kidneys. Here we use metabolomics profiling (592 fasting serum metabolites) to identify molecular markers and pathways associated with serum electrolyte levels in two independent population-based cohorts. We included 1523 adults from TwinsUK not on blood pressure-lowering therapy and without renal impairment to look for metabolites associated with chloride, sodium, potassium and bicarbonate by running linear mixed models adjusting for covariates and multiple comparisons. For each electrolyte, we further performed pathway enrichment analysis (PAGE algorithm). Results were replicated in an independent cohort. Chloride, potassium, bicarbonate and sodium associated with 10, 58, 36 and 17 metabolites respectively (each P < 2.1 × 10-5), mainly lipids. Of all the electrolytes, serum potassium showed the most significant associations with individual fatty acid metabolites and specific enrichment of fatty acid pathways. In contrast, serum sodium and bicarbonate showed associations predominantly with amino-acid related species. In the first study to examine systematically associations between serum electrolytes and small circulating molecules, we identified novel metabolites and metabolic pathways associated with serum electrolyte levels. The role of these metabolic pathways on electrolyte homeostasis merits further studies.

Characterization of Bulk Phosphatidylcholine Compositions in Human Plasma Using Side-Chain Resolving Lipidomics.

Kit-based assays, such as AbsoluteIDQTM p150, are widely used in large cohort studies and provide a standardized method to quantify blood concentrations of phosphatidylcholines (PCs). Many disease-relevant associations of PCs were reported using this method. However, their interpretation is hampered by lack of functionally-relevant information on the detailed fatty acid side-chain compositions as only the total number of carbon atoms and double bonds is identified by the kit. To enable more substantiated interpretations, we characterized these PC sums using the side-chain resolving LipidyzerTM platform, analyzing 223 samples in parallel to the AbsoluteIDQTM. Combining these datasets, we estimated the quantitative composition of PC sums and subsequently tested their replication in an independent cohort. We identified major constituents of 28 PC sums, revealing also various unexpected compositions. As an example, PC 16:0_22:5 accounted for more than 50% of the PC sum with in total 38 carbon atoms and 5 double bonds (PC aa 38:5). For 13 PC sums, we found relatively high abundances of odd-chain fatty acids. In conclusion, our study provides insights in PC compositions in human plasma, facilitating interpretation of existing epidemiological data sets and potentially enabling imputation of PC compositions for future meta-analyses of lipidomics data.

Caloric Restriction Alters Postprandial Responses of Essential Brain Metabolites in Young Adult Mice.

Caloric restriction (CR) has been shown to extend longevity and protect brain function in aging. However, the effects of CR in young adult mice remain largely unexplored. In addition to the fundamental, long-term changes, recent studies demonstrate that CR has a significant impact on transient, postprandial metabolic flexibility and turnover compared to control groups. The goal of this study was to identify the brain metabolic changes at a transient (2 h) and steady (6 h) postprandial state in young mice (5-6 months of age) fed with CR or ad libitum (AL; free eating). Using metabolomics profiling, we show that CR mice had significantly higher levels of neurotransmitters (e.g., glutamate, N-acetylglutamate), neuronal integrity markers (e.g., NAA and NAAG), essential fatty acids (e.g., DHA and DPA), and biochemicals associated carnitine metabolism (related to reduced oxidative stress and inflammation) in the cerebral cortex and hippocampus at 2-h. These biochemicals remained at high levels at the 6-h postprandial time-point. The AL mice did not show the similar increases in essential fatty acid and carnitine metabolism until the 6-h time-point, and failed to show increases in neurotransmitters and neuronal integrity markers at any time-point. On the other hand, metabolites related to glucose utilization-glycolysis and pentose phosphate pathway (PPP)-were low in the CR mice throughout the 6-h period and significantly increased at the 6-h time-point in the AL mice. Our findings suggest that CR induces distinct postprandial responses in metabolites that are essential to maintain brain functions. CR mice produced higher levels of essential brain metabolites in a shorter period after a meal and sustained the levels for an extended period, while maintaining a lower level of glucose utilization. These early brain metabolism changes in the CR mice might play a critical role for neuroprotection in aging. Understanding the interplay between dietary intervention and postprandial metabolic responses from an early age may have profound implications for impeding brain aging and reducing risk for neurodegenerative disorders.

Metabolomics Identifies Novel Blood Biomarkers of Pulmonary Function and COPD in the General Population.

Determination of metabolomic signatures of pulmonary function and chronic obstructive pulmonary disease (COPD) in the general population could aid in identification and understanding of early disease processes. Metabolome measurements were performed on serum from 4742 individuals (2354 African-Americans and 1529 European-Americans from the Atherosclerosis Risk in Communities study and 859 Europeans from the Cooperative Health Research in the Region of Augsburg study). We examined 368 metabolites in relation to cross-sectional measures of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), their ratio (FEV1/FVC) and COPD using multivariable regression followed by meta-analysis. At a false discovery rate of 0.05, 95 metabolites were associated with FEV1 and 100 with FVC (73 overlapping), including inverse associations with branched-chain amino acids and positive associations with glutamine. Ten metabolites were associated with FEV1/FVC and seventeen with COPD (393 cases). Enriched pathways of amino acid metabolism were identified. Associations with FEV1 and FVC were not driven by individuals with COPD. We identified novel metabolic signatures of pulmonary function and COPD in African and European ancestry populations. These may allow development of biomarkers in the general population of early disease pathogenesis, before pulmonary function has decreased to levels diagnostic for COPD.

Circulating levels of the anti-oxidant indoleproprionic acid are associated with higher gut microbiome diversity.

The gut microbiome has recently emerged as an important regulator of insulin resistance and abdominal obesity. The tryptophan metabolite generated by the gut microbiome, indoleproprionic acid (IPA) has been shown to predict the onset of type 2 diabetes. IPA is a metabolite produced by gut microbes from dietary tryptophan that exhibits a high degree of inter-individual variation. The microbiome composition parameters that are associated with circulating levels of this potent anti-oxidant have however not been investigated to date in human populations. In 1018 middle-aged women from the TwinsUK cohort, we assessed the relationship between serum IPA levels and gut microbiome composition targeting the 16S rRNA gene. Microbiome alpha-diversity was positively correlated with serum indoleproprionic acid levels (Shannon Diversity: Beta[95%CI] = 0.19[0.13;0.25], P = 6.41 × 10-10) after adjustment for covariates. Sixteen taxa and 12 operational taxonomic units (OTUs) associated with IPA serum levels. Among these are positive correlations with the butyrate-producing Faecalibacterium prausnitzii, the class Mollicutes and the order RF39 of the Tenericutes, and Coprococcus Negative correlations instead were observed with Eubacterium dolichum previously shown to correlate with visceral fat mass and several genera in the Lachnospiraceae family such as Blautia and Ruminococcus previously shown to correlate with obesity. Microbiome composition parameters explained ~20% of the variation in circulating levels of IPA, whereas nutritional and host genetic parameters explained only ~4%. Our data confirm an association between IPA circulating levels and metabolic syndrome parameters and indicate that gut microbiome composition influences IPA levels.

Metabolomics-based identification of metabolic alterations in PARK2.

Objective: Parkin is the causative gene for autosomal recessive familial Parkinson's disease (PD), although it remains unclear how parkin dysfunction is involved with the general condition. Recently, serum and/or plasma metabolomics revealed alterations in metabolic pathways that might reflect pathomechanisms of idiopathic PD (iPD). Thus, we hypothesized that serum metabolomics of patients with homozygous or compound heterozygous parkin mutations (namely, PARK2) might reflect metabolic alterations due to parkin dysfunction. Methods: We enrolled 15 PARK2 patients (52 ± 17.6 years) confirmed with homozygous (seven cases) and compound heterozygous (eight cases) parkin mutations, along with 19 healthy age-matched controls (51 ± 11.5 years). We analyzed 830 metabolites from participants' serum using well-established metabolomics technologies, including ultra-high performance liquid chromatography/tandem mass spectroscopy. Results: Based on metabolic profiles, hierarchical matrix analysis can divide samples between control and PARK2 subjects. Profiles from PARK2 patients showed significantly higher levels of fatty acid (FA) metabolites and oxidized lipids, and significantly lower levels of antioxidant, caffeine, and benzoate-related metabolites. Interpretation: Metabolomics can identify specific metabolic alterations in PARK2 patients compared with controls. Alterations in FA metabolites suggest a relationship between parkin function and lipid metabolism. The elevation of oxidized lipids in combination with decreasing antioxidants may reflect general hyperoxidative stress. Decreasing benzoate-related metabolites might be due to the alteration in gut microbiota. Consequently, caffeine and its metabolites may be decreased due to malabsorption. These findings are similar to metabolic alterations in iPD. Thus, serum/plasma metabolomics may reflect the association between parkin dysfunction and parkinsonism.

Metabolite changes in blood predict the onset of tuberculosis.

New biomarkers of tuberculosis (TB) risk and disease are critical for the urgently needed control of the ongoing TB pandemic. In a prospective multisite study across Subsaharan Africa, we analyzed metabolic profiles in serum and plasma from HIV-negative, TB-exposed individuals who either progressed to TB 3-24 months post-exposure (progressors) or remained healthy (controls). We generated a trans-African metabolic biosignature for TB, which identifies future progressors both on blinded test samples and in external data sets and shows a performance of 69% sensitivity at 75% specificity in samples within 5 months of diagnosis. These prognostic metabolic signatures are consistent with development of subclinical disease prior to manifestation of active TB. Metabolic changes associated with pre-symptomatic disease are observed as early as 12 months prior to TB diagnosis, thus enabling timely interventions to prevent disease progression and transmission.

The potential of metabolic profiling for vaccine development.

Recent technological advances have provided deeper insights into the role of small molecules in biological processes. Metabolic profiling has thus entered the arena of -omics studies and rapidly proven its value both as stand-alone and as complement to other more advanced approaches, notably transcriptomics. Here we describe the potential of metabolic profiling for vaccinology embedded in the context of infection and immunity. This discussion is preceded by a description of the relevant technical and analytical tools for biological interpretation of metabolic data. Although not as widely applied as other -omics technologies, we believe that metabolic profiling can make important contributions to the better understanding of mechanisms underlying vaccine-induced responses and their effects on the prevention of infection or disease.

The fecal metabolome as a functional readout of the gut microbiome.

The human gut microbiome plays a key role in human health 1 , but 16S characterization lacks quantitative functional annotation 2 . The fecal metabolome provides a functional readout of microbial activity and can be used as an intermediate phenotype mediating host-microbiome interactions 3 . In this comprehensive description of the fecal metabolome, examining 1,116 metabolites from 786 individuals from a population-based twin study (TwinsUK), the fecal metabolome was found to be only modestly influenced by host genetics (heritability (H2) = 17.9%). One replicated locus at the NAT2 gene was associated with fecal metabolic traits. The fecal metabolome largely reflects gut microbial composition, explaining on average 67.7% (±18.8%) of its variance. It is strongly associated with visceral-fat mass, thereby illustrating potential mechanisms underlying the well-established microbial influence on abdominal obesity. Fecal metabolic profiling thus is a novel tool to explore links among microbiome composition, host phenotypes, and heritable complex traits.