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.

Ozone Exposure Increases Circulating Stress Hormones and Lipid Metabolites in Humans.

RATIONALE: Air pollution has been associated with increased prevalence of type 2 diabetes; however, the mechanisms remain unknown. We have shown that acute ozone exposure in rats induces release of stress hormones, hyperglycemia, leptinemia, and glucose intolerance that are associated with global changes in peripheral glucose, lipid, and amino acid metabolism. OBJECTIVES: To examine ozone-induced metabolic derangement in humans using serum metabolomic assessment, establish human-to-rodent coherence, and identify novel nonprotein biomarkers. METHODS: Serum samples were obtained from a crossover clinical study that included two clinic visits (n = 24 each) where each subject was blindly exposed in the morning to either filtered air or 0.3 parts per million ozone for 2 hours during 15-minute on-off exercise. Serum samples collected within 1 hour after exposure were assessed for changes in metabolites using a metabolomic approach. MEASUREMENTS AND MAIN RESULTS: Metabolomic analysis revealed that ozone exposure markedly increased serum cortisol and corticosterone together with increases in monoacylglycerol, glycerol, and medium- and long-chain free fatty acids, reflective of lipid mobilization and catabolism. Additionally, ozone exposure increased serum lysolipids, potentially originating from membrane lipid breakdown. Ozone exposure also increased circulating mitochondrial ß-oxidation-derived metabolites, such as acylcarnitines, together with increases in the ketone body 3-hydroxybutyrate. These changes suggested saturation of ß-oxidation by ozone in exercising humans. CONCLUSIONS: As in rodents, acute ozone exposure increased stress hormones and globally altered peripheral lipid metabolism in humans, likely through activation of a neurohormonally mediated stress response pathway. The metabolomic assessment revealed new biomarkers and allowed for establishment of rodent-to-human coherence. Clinical trial registered with www.clinicaltrials.gov (NCT 01492517).

Urine Metabolite Profiles Predictive of Human Kidney Allograft Status.

Noninvasive diagnosis and prognostication of acute cellular rejection in the kidney allograft may help realize the full benefits of kidney transplantation. To investigate whether urine metabolites predict kidney allograft status, we determined levels of 749 metabolites in 1516 urine samples from 241 kidney graft recipients enrolled in the prospective multicenter Clinical Trials in Organ Transplantation-04 study. A metabolite signature of the ratio of 3-sialyllactose to xanthosine in biopsy specimen-matched urine supernatants best discriminated acute cellular rejection biopsy specimens from specimens without rejection. For clinical application, we developed a high-throughput mass spectrometry-based assay that enabled absolute and rapid quantification of the 3-sialyllactose-to-xanthosine ratio in urine samples. A composite signature of ratios of 3-sialyllactose to xanthosine and quinolinate to X-16397 and our previously reported urinary cell mRNA signature of 18S ribosomal RNA, CD3ε mRNA, and interferon-inducible protein-10 mRNA outperformed the metabolite signatures and the mRNA signature. The area under the receiver operating characteristics curve for the composite metabolite-mRNA signature was 0.93, and the signature was diagnostic of acute cellular rejection with a specificity of 84% and a sensitivity of 90%. The composite signature, developed using solely biopsy specimen-matched urine samples, predicted future acute cellular rejection when applied to pristine samples taken days to weeks before biopsy. We conclude that metabolite profiling of urine offers a noninvasive means of diagnosing and prognosticating acute cellular rejection in the human kidney allograft, and that the combined metabolite and mRNA signature is diagnostic and prognostic of acute cellular rejection with very high accuracy.

Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis.

BACKGROUND: Higher circulating levels of the branched-chain amino acids (BCAAs; i.e., isoleucine, leucine, and valine) are strongly associated with higher type 2 diabetes risk, but it is not known whether this association is causal. We undertook large-scale human genetic analyses to address this question. METHODS AND FINDINGS: Genome-wide studies of BCAA levels in 16,596 individuals revealed five genomic regions associated at genome-wide levels of significance (p < 5 × 10-8). The strongest signal was 21 kb upstream of the PPM1K gene (beta in standard deviations [SDs] of leucine per allele = 0.08, p = 3.9 × 10-25), encoding an activator of the mitochondrial branched-chain alpha-ketoacid dehydrogenase (BCKD) responsible for the rate-limiting step in BCAA catabolism. In another analysis, in up to 47,877 cases of type 2 diabetes and 267,694 controls, a genetically predicted difference of 1 SD in amino acid level was associated with an odds ratio for type 2 diabetes of 1.44 (95% CI 1.26-1.65, p = 9.5 × 10-8) for isoleucine, 1.85 (95% CI 1.41-2.42, p = 7.3 × 10-6) for leucine, and 1.54 (95% CI 1.28-1.84, p = 4.2 × 10-6) for valine. Estimates were highly consistent with those from prospective observational studies of the association between BCAA levels and incident type 2 diabetes in a meta-analysis of 1,992 cases and 4,319 non-cases. Metabolome-wide association analyses of BCAA-raising alleles revealed high specificity to the BCAA pathway and an accumulation of metabolites upstream of branched-chain alpha-ketoacid oxidation, consistent with reduced BCKD activity. Limitations of this study are that, while the association of genetic variants appeared highly specific, the possibility of pleiotropic associations cannot be entirely excluded. Similar to other complex phenotypes, genetic scores used in the study captured a limited proportion of the heritability in BCAA levels. Therefore, it is possible that only some of the mechanisms that increase BCAA levels or affect BCAA metabolism are implicated in type 2 diabetes. CONCLUSIONS: Evidence from this large-scale human genetic and metabolomic study is consistent with a causal role of BCAA metabolism in the aetiology of type 2 diabetes.

Senescent human fibroblasts show increased glycolysis and redox homeostasis with extracellular metabolomes that overlap with those of irreparable DNA damage, aging, and disease.

Cellular senescence can modulate various pathologies and is associated with irreparable DNA double-strand breaks (IrrDSBs). Extracellular senescence metabolomes (ESMs) were generated from fibroblasts rendered senescent by proliferative exhaustion (PEsen) or 20 Gy of γ rays (IrrDSBsen) and compared with those of young proliferating cells, confluent cells, quiescent cells, and cells exposed to repairable levels of DNA damage to identify novel noninvasive markers of senescent cells. ESMs of PEsen and IrrDSBsen overlapped and showed increased levels of citrate, molecules involved in oxidative stress, a sterol, monohydroxylipids, tryptophan metabolism, phospholipid, and nucleotide catabolism, as well as reduced levels of dipeptides containing branched chain amino acids. The ESM overlaps with the aging and disease body fluid metabolomes, supporting their utility in the noninvasive detection of human senescent cells in vivo and by implication the detection of a variety of human pathologies. Intracellular metabolites of senescent cells showed a relative increase in glycolysis, gluconeogenesis, the pentose-phosphate pathway, and, consistent with this, pyruvate dehydrogenase kinase transcripts. In contrast, tricarboxylic acid cycle enzyme transcript levels were unchanged and their metabolites were depleted. These results are surprising because glycolysis antagonizes senescence entry but are consistent with established senescent cells entering a state of low oxidative stress.

A systems view of type 2 diabetes-associated metabolic perturbations in saliva, blood and urine at different timescales of glycaemic control.

AIMS/HYPOTHESIS: Metabolomics has opened new avenues for studying metabolic alterations in type 2 diabetes. While many urine and blood metabolites have been associated individually with diabetes, a complete systems view analysis of metabolic dysregulations across multiple biofluids and over varying timescales of glycaemic control is still lacking. METHODS: Here we report a broad metabolomics study in a clinical setting, covering 2,178 metabolite measures in saliva, blood plasma and urine from 188 individuals with diabetes and 181 controls of Arab and Asian descent. Using multivariate linear regression we identified metabolites associated with diabetes and markers of acute, short-term and long-term glycaemic control. RESULTS: Ninety-four metabolite associations with diabetes were identified at a Bonferroni level of significance (p < 2.3 × 10(-5)), 16 of which have never been reported. Sixty-five of these diabetes-associated metabolites were associated with at least one marker of glycaemic control in the diabetes group. Using Gaussian graphical modelling, we constructed a metabolic network that links diabetes-associated metabolites from three biofluids across three different timescales of glycaemic control. CONCLUSIONS/INTERPRETATION: Our study reveals a complex network of biochemical dysregulation involving metabolites from different pathways of diabetes pathology, and provides a reference framework for future diabetes studies with metabolic endpoints.

Metabolomic analysis of prostate cancer risk in a prospective cohort: The alpha-tocolpherol, beta-carotene cancer prevention (ATBC) study.

Despite decades of concerted epidemiological research, relatively little is known about the etiology of prostate cancer. As genome-wide association studies have identified numerous genetic variants, so metabolomic profiling of blood and other tissues represents an agnostic, "broad-spectrum" approach for examining potential metabolic biomarkers of prostate cancer risk. To this end, we conducted a prospective analysis of prostate cancer within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort based on 200 cases (100 aggressive) and 200 controls (age- and blood collection date-matched) with fasting serum collected up to 20 years prior to case diagnoses. Ultrahigh performance liquid chromatography/mass spectroscopy and gas chromatography/mass spectroscopy identified 626 compounds detected in >95% of the men and the odds ratio per 1-standard deviation increase in log-metabolite levels and risk were estimated using conditional logistic regression. We observed strong inverse associations between energy and lipid metabolites and aggressive cancer (p = 0.018 and p = 0.041, respectively, for chemical class over-representation). Inositol-1-phosphate showed the strongest association (OR = 0.56, 95% CI = 0.39-0.81, p = 0.002) and glycerophospholipids and fatty acids were heavily represented; e.g., oleoyl-linoleoyl-glycerophosphoinositol (OR = 0.64, p = 0.004), 1-stearoylglycerophosphoglycerol (OR=0.65, p = 0.025), stearate (OR=0.65, p = 0.010) and docosadienoate (OR = 0.66, p = 0.014). Both alpha-ketoglutarate and citrate were associated with aggressive disease risk (OR = 0.69, 95% CI = 0.51-0.94, p = 0.02; OR = 0.69, 95% CI = 0.50-0.95, p = 0.02), as were elevated thyroxine and trimethylamine oxide (OR = 1.65, 95% CI = 1.08-2.54, p = 0.021; and OR = 1.36, 95% CI = 1.02-1.81, p = 0.039). Serum PSA adjustment did not alter the findings. Our data reveal several metabolomic leads that may have pathophysiological relevance to prostate carcinogenesis and should be examined through additional research.

Metabolomics of dates (Phoenix dactylifera) reveals a highly dynamic ripening process accounting for major variation in fruit composition.

BACKGROUND: Dates are tropical fruits with appreciable nutritional value. Previous attempts at global metabolic characterization of the date metabolome were constrained by small sample size and limited geographical sampling. In this study, two independent large cohorts of mature dates exhibiting substantial diversity in origin, varieties and fruit processing conditions were measured by metabolomics techniques in order to identify major determinants of the fruit metabolome. RESULTS: Multivariate analysis revealed a first principal component (PC1) significantly associated with the dates' countries of production. The availability of a smaller dataset featuring immature dates from different development stages served to build a model of the ripening process in dates, which helped reveal a strong ripening signature in PC1. Analysis revealed enrichment in the dry type of dates amongst fruits with early ripening profiles at one end of PC1 as oppose to an overrepresentation of the soft type of dates with late ripening profiles at the other end of PC1. Dry dates are typical to the North African region whilst soft dates are more popular in the Gulf region, which partly explains the observed association between PC1 and geography. Analysis of the loading values, expressing metabolite correlation levels with PC1, revealed enrichment patterns of a comprehensive range of metabolite classes along PC1. Three distinct metabolic phases corresponding to known stages of date ripening were observed: An early phase enriched in regulatory hormones, amines and polyamines, energy production, tannins, sucrose and anti-oxidant activity, a second phase with on-going phenylpropanoid secondary metabolism, gene expression and phospholipid metabolism and a late phase with marked sugar dehydration activity and degradation reactions leading to increased volatile synthesis. CONCLUSIONS: These data indicate the importance of date ripening as a main driver of variation in the date metabolome responsible for their diverse nutritional and economical values. The biochemistry of the ripening process in dates is consistent with other fruits but natural dryness may prevent degenerative senescence in dates following ripening. Based on the finding that mature dates present varying extents of ripening, our survey of the date metabolome essentially revealed snapshots of interchanging metabolic states during ripening empowering an in-depth characterization of underlying biology.

Metabolic signatures differentiate ovarian from colon cancer cell lines.

BACKGROUND: In this era of precision medicine, the deep and comprehensive characterization of tumor phenotypes will lead to therapeutic strategies beyond classical factors such as primary sites or anatomical staging. Recently, "-omics" approached have enlightened our knowledge of tumor biology. Such approaches have been extensively implemented in order to provide biomarkers for monitoring of the disease as well as to improve readouts of therapeutic impact. The application of metabolomics to the study of cancer is especially beneficial, since it reflects the biochemical consequences of many cancer type-specific pathophysiological processes. Here, we characterize metabolic profiles of colon and ovarian cancer cell lines to provide broader insight into differentiating metabolic processes for prospective drug development and clinical screening. METHODS: We applied non-targeted metabolomics-based mass spectroscopy combined with ultrahigh-performance liquid chromatography and gas chromatography for the metabolic phenotyping of four cancer cell lines: two from colon cancer (HCT15, HCT116) and two from ovarian cancer (OVCAR3, SKOV3). We used the MetaP server for statistical data analysis. RESULTS: A total of 225 metabolites were detected in all four cell lines; 67 of these molecules significantly discriminated colon cancer from ovarian cancer cells. Metabolic signatures revealed in our study suggest elevated tricarboxylic acid cycle and lipid metabolism in ovarian cancer cell lines, as well as increased ß-oxidation and urea cycle metabolism in colon cancer cell lines. CONCLUSIONS: Our study provides a panel of distinct metabolic fingerprints between colon and ovarian cancer cell lines. These may serve as potential drug targets, and now can be evaluated further in primary cells, biofluids, and tissue samples for biomarker purposes.

Inhaled ozone (O3)-induces changes in serum metabolomic and liver transcriptomic profiles in rats.

Air pollution has been linked to increased incidence of diabetes. Recently, we showed that ozone (O3) induces glucose intolerance, and increases serum leptin and epinephrine in Brown Norway rats. In this study, we hypothesized that O3 exposure will cause systemic changes in metabolic homeostasis and that serum metabolomic and liver transcriptomic profiling will provide mechanistic insights. In the first experiment, male Wistar Kyoto (WKY) rats were exposed to filtered air (FA) or O3 at 0.25, 0.50, or 1.0ppm, 6h/day for two days to establish concentration-related effects on glucose tolerance and lung injury. In a second experiment, rats were exposed to FA or 1.0ppm O3, 6h/day for either one or two consecutive days, and systemic metabolic responses were determined immediately after or 18h post-exposure. O3 increased serum glucose and leptin on day 1. Glucose intolerance persisted through two days of exposure but reversed 18h-post second exposure. O3 increased circulating metabolites of glycolysis, long-chain free fatty acids, branched-chain amino acids and cholesterol, while 1,5-anhydroglucitol, bile acids and metabolites of TCA cycle were decreased, indicating impaired glycemic control, proteolysis and lipolysis. Liver gene expression increased for markers of glycolysis, TCA cycle and gluconeogenesis, and decreased for markers of steroid and fat biosynthesis. Genes involved in apoptosis and mitochondrial function were also impacted by O3. In conclusion, short-term O3 exposure induces global metabolic derangement involving glucose, lipid, and amino acid metabolism, typical of a stress-response. It remains to be examined if these alterations contribute to insulin resistance upon chronic exposure.

Licofelone modulates neuroinflammation and attenuates mechanical hypersensitivity in the chronic phase of spinal cord injury.

Inflammation is a major factor shaping outcome during the early, acute phase of traumatic spinal cord injury (SCI). It is known that pro-inflammatory signaling within the injured spinal cord drives pathological alterations in neurosensory processing and shapes functional outcome early after injury. However, it is unclear whether inflammation persists into the chronic phase of injury or shapes sensory processing long after injury. To investigate these possibilities, we have performed biochemical and behavioral assessments 9 months after moderate thoracic spinal contusion injury in the rat. We have found that levels of the pro-inflammatory lipid mediators leukotriene B4 and prostaglandin E2 are elevated in the chronic spinal cord lesion site. Additionally, using metabolomic profiling, we have detected elevated levels of pro-oxidative and inflammatory metabolites, along with alterations in multiple biological pathways within the chronic lesion site. We found that 28 d treatment of chronically injured rats with the dual COX/5-LOX inhibitor licofelone elevated levels of endogenous anti-oxidant and anti-inflammatory metabolites within the lesion site. Furthermore, licofelone treatment reduced hypersensitivity of hindpaws to mechanical, but not thermal, stimulation, indicating that mechanical sensitivity is modulated by pro-inflammatory signaling in the chronic phase of injury. Together, these findings provide novel evidence of inflammation and oxidative stress within spinal cord tissue far into the chronic phase of SCI, and demonstrate a role for inflammatory modulation of mechanical sensitivity in the chronic phase of injury.

Uremic solutes and risk of end-stage renal disease in type 2 diabetes: metabolomic study.

Here we studied plasma metabolomic profiles as determinants of progression to end-stage renal disease (ESRD) in patients with type 2 diabetes (T2D). This nested case-control study evaluated 40 cases who progressed to ESRD during 8-12 years of follow-up and 40 controls who remained alive without ESRD from the Joslin Kidney Study cohort. Controls were matched with cases for baseline clinical characteristics, although controls had slightly higher eGFR and lower levels of urinary albumin excretion than cases. Plasma metabolites at baseline were measured by mass spectrometry-based global metabolomic profiling. Of the named metabolites in the library, 262 were detected in at least 80% of the study patients. The metabolomic platform recognized 78 metabolites previously reported to be elevated in ESRD (uremic solutes). Sixteen were already elevated in the baseline plasma of our cases years before ESRD developed. Other uremic solutes were either not different or not commonly detectable. Essential amino acids and their derivatives were significantly depleted in the cases, whereas certain amino acid-derived acylcarnitines were increased. All findings remained statistically significant after adjustment for differences between study groups in albumin excretion rate, eGFR, or HbA1c. Uremic solute differences were confirmed by quantitative measurements. Thus, abnormal plasma concentrations of putative uremic solutes and essential amino acids either contribute to progression to ESRD or are a manifestation of an early stage(s) of the disease process that leads to ESRD in T2D.

Profiling the effects of isocitrate dehydrogenase 1 and 2 mutations on the cellular metabolome.

Point mutations of the NADP(+)-dependent isocitrate dehydrogenases 1 and 2 (IDH1 and IDH2) occur early in the pathogenesis of gliomas. When mutated, IDH1 and IDH2 gain the ability to produce the metabolite (R)-2-hydroxyglutarate (2HG), but the downstream effects of mutant IDH1 and IDH2 proteins or of 2HG on cellular metabolism are unknown. We profiled >200 metabolites in human oligodendroglioma (HOG) cells to determine the effects of expression of IDH1 and IDH2 mutants. Levels of amino acids, glutathione metabolites, choline derivatives, and tricarboxylic acid (TCA) cycle intermediates were altered in mutant IDH1- and IDH2-expressing cells. These changes were similar to those identified after treatment of the cells with 2HG. Remarkably, N-acetyl-aspartyl-glutamate (NAAG), a common dipeptide in brain, was 50-fold reduced in cells expressing IDH1 mutants and 8.3-fold reduced in cells expressing IDH2 mutants. NAAG also was significantly lower in human glioma tissues containing IDH mutations than in gliomas without such mutations. These metabolic changes provide clues to the pathogenesis of tumors associated with IDH gene mutations.

SLC17 transporters mediate renal excretion of Lac-Phe in mice and humans.

N-lactoyl-phenylalanine (Lac-Phe) is a lactate-derived metabolite that suppresses food intake and body weight. Little is known about the mechanisms that mediate Lac-Phe transport across cell membranes. Here we identify SLC17A1 and SLC17A3, two kidney-restricted plasma membrane-localized solute carriers, as physiologic urine Lac-Phe transporters. In cell culture, SLC17A1/3 exhibit high Lac-Phe efflux activity. In humans, levels of Lac-Phe in urine exhibit a strong genetic association with the SLC17A1-4 locus. Urine Lac-Phe levels are also increased following a Wingate sprint test. In mice, genetic ablation of either SLC17A1 or SLC17A3 reduces urine Lac-Phe levels. Despite these differences, both knockout strains have normal blood Lac-Phe and body weights, demonstrating that urine and plasma Lac-Phe pools are functionally and biochemically de-coupled. Together, these data establish SLC17 family members as the physiologic urine transporters for Lac-Phe and uncover a biochemical pathway for the renal excretion of this signaling metabolite.

HuR is a post-transcriptional regulator of core metabolic enzymes in pancreatic cancer.

Cancer cell metabolism differs from normal cells, yet the regulatory mechanisms responsible for these differences are incompletely understood, particularly in response to acute changes in the tumor microenvironment. HuR, an RNA-binding protein, acts under acute stress to regulate core signaling pathways in cancer through post-transcriptional regulation of mRNA targets. We demonstrate that HuR regulates the metabolic phenotype in pancreatic cancer cells and is critical for survival under acute glucose deprivation. Using three pancreatic cancer cell line models, HuR-proficient cells demonstrated superior survival under glucose deprivation when compared with isogenic cells with siRNA-silencing of HuR expression (HuR-deficient cells). We found that HuR-proficient cells utilized less glucose, but produced greater lactate, as compared with HuR-deficient cells. Acute glucose deprivation was found to act as a potent stimulus for HuR translocation from the nucleus to the cytoplasm, where HuR stabilizes its mRNA targets. We performed a gene expression array on ribonucleoprotein-immunoprecipitated mRNAs bound to HuR and identified 11 novel HuR target transcripts that encode enzymes central to glucose metabolism. Three (GPI, PRPS2 and IDH1) were selected for validation studies, and confirmed as bona fide HuR targets. These findings establish HuR as a critical regulator of pancreatic cancer cell metabolism and survival under acute glucose deprivation. Further explorations into HuR's role in cancer cell metabolism should uncover novel therapeutic targets that are critical for cancer cell survival in a metabolically compromised tumor microenvironment.

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.

Comparison of gene expression profiles induced by coarse, fine, and ultrafine particulate matter.

Coarse, fine, and ultrafine particulate matter (PM) fractions possess different physical properties and chemical compositions and may produce different adverse health effects. Studies were undertaken to determine whether or not gene expression patterns may be used to discriminate among the three size fractions. Airway epithelial cells obtained from 6 normal individuals were exposed to Chapel Hill coarse, fine or ultrafine PM (250 µg/ml) for 6 and 24 h (n=3 different individuals each). RNA was isolated and hybridized to Affymetrix cDNA microarrays. Significant genes were identified and mapped to canonical pathways. Expression of selected genes was confirmed by reverse-transcription polymerase chain reaction (RT-PCR). The numbers of genes altered by coarse, fine, and ultrafine PM increased from 0, 6, and 17 at 6 h to 1281, 302, and 455 at 24 h, respectively. The NRF2-mediated oxidative stress response, cell cycle:G2/M DNA damage checkpoint regulation, and mitotic roles of polo-like kinase were the top three pathways altered by all three fractions. Fine and ultrafine PM displayed more similar gene expression patterns. One example was the increased expression of metallothionein isoforms, reflecting the higher zinc content associated with fine and ultrafine fractions. A set of 10 genes was identified that could discriminate fine and ultrafine PM from coarse PM. These results indicate that common properties shared by the three size fractions as well as size-specific factors, e.g., compositions, may determine the effects on gene expression. Genomic markers may be used to discriminate coarse from fine and ultrafine PM.

Metabolomic differences in heart failure patients with and without major depression.

Metabolomics is an emerging technology that allows researchers to characterize hundreds of small molecules that comprise the metabolome. We sought to determine metabolic differences in depressed and nondepressed participants. The sample consisted of a depressed group of patients with heart failure enrolled in an NIMH-supported clinical trial of sertraline versus placebo in depressed heart failure patients, and a nondepressed comparator group of heart failure patients. Plasma was obtained from blood samples provided by participants at baseline, and samples were profiled on GC-MS and LC-MS metabolomics platforms for biochemical content. A number of biochemicals were significantly different between groups, with depressed participants showing higher concentrations of several amino acids and dicarboxylic fatty acids. These results are consistent with prior findings where changes in neurotransmitter systems and fatty acid metabolism were shown to associate with the depressed state. It is unclear what role heart failure may have played in these differing concentrations.