Metabolite profiling is being increasing employed in the study of prostate cancer as a means of identifying predictive, diagnostic, and prognostic biomarkers. This review provides a summary and critique of the current literature. Thirty-three human case–control studies of prostate cancer exploring disease prediction, diagnosis, progression, or treatment response were identified. All but one demonstrated the ability of metabolite profiling to distinguish cancer from benign, tumor aggressiveness, cases who recurred, and those who responded well to therapy. In the subset of studies where biomarker discriminatory ability was quantified, high AUCs were reported that would potentially outperform the current gold standards in diagnosis, prognosis, and disease recurrence, including PSA testing. There were substantial similarities between the metabolites and the associated pathways reported as significant by independent studies, and important roles for abnormal cell growth, intensive cell proliferation, and dysregulation of lipid metabolism were highlighted. The weight of the evidence therefore suggests metabolic alterations specific to prostate carcinogenesis and progression that may represent potential metabolic biomarkers. However, replication and validation of the most promising biomarkers is currently lacking and a number of outstanding methodologic issues remain to be addressed to maximize the utility of metabolomics in the study of prostate cancer. Cancer Epidemiol Biomarkers Prev; 25(6); 887–906. ©2016 AACR.

In this review, we discuss the growing literature demonstrating robust and pervasive associations between the microbiome and metabolome. We focus on the gut microbiome, which harbors the taxonomically most diverse and the largest collection of microorganisms in the human body. Methods for integrative analysis of these “omics” are under active investigation and we discuss the advances and challenges in the combined use of metabolomics and microbiome data. Findings from large consortia, including the Human Microbiome Project and Metagenomics of the Human Intestinal Tract (MetaHIT) and others demonstrate the impact of microbiome-metabolome interactions on human health. Mechanisms whereby the microbes residing in the human body interact with metabolites to impact disease risk are beginning to be elucidated, and discoveries in this area will likely be harnessed to develop preventive and treatment strategies for complex diseases.

Background: Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood.Objectives: We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature.Methods: We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM_2.5, NO₂, O₃, and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures.Results: Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m². Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM_2.5, 15 metabolites with NO₂, and 6 metabolites with temperature) while no metabolites were associated with O₃. One out of five ICA factors (factor 2) was significantly associated with PM_2.5. We identified eight perturbed metabolic pathways with long-term exposure to PM_2.5and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair.Conclusions: Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM_2.5, NO₂and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.

Rationale: A link among sphingolipids, 17q21 genetic variants, and childhood asthma has been suggested, but the underlying mechanisms and characteristics of such an asthma endotype remain to be elucidated. Objectives: To study the sphingolipid-associated childhood asthma endotype using multiomic data. Methods: We used untargeted liquid chromatography–mass spectrometry plasma metabolomic profiles at the ages of 6 months and 6 years from more than 500 children in the COPSAC2010 (Copenhagen Prospective Studies on Asthma in Childhood) birth cohort focusing on sphingolipids, and we integrated the 17q21 genotype and nasal gene expression of SPT (serine palmitoyl-CoA transferase) (i.e., the rate-limiting enzyme in de novo sphingolipid synthesis) in relation to asthma development and lung function traits from infancy until the age 6 years. Replication was sought in the independent VDAART (Vitamin D Antenatal Asthma Reduction Trial) cohort. Measurements and Main Results: Lower concentrations of ceramides and sphingomyelins at the age of 6 months were associated with an increased risk of developing asthma before age 3, which was also observed in VDAART. At the age of 6 years, lower concentrations of key phosphosphingolipids (e.g., sphinganine-1-phosphate) were associated with increased airway resistance. This relationship was dependent on the 17q21 genotype and nasal SPT gene expression, with significant interactions occurring between the genotype and the phosphosphingolipid concentrations and between the genotype and SPT expression, in which lower phosphosphingolipid concentrations and reduced SPT expression were associated with increasing numbers of at-risk alleles. However, the findings did not pass the false discovery rate threshold of <0.05. Conclusions: This exploratory study suggests the existence of a childhood asthma endotype with early onset and increased airway resistance that is characterized by reduced sphingolipid concentrations, which are associated with 17q21 genetic variants and expression of the SPT enzyme.