Recurrent Clostridium difficile infection associates with distinct bile acid and microbiome profiles

Background: The healthy microbiome protects against the development of Clostridium difficile infection (CDI), which typically develops following antibiotics. The microbiome metabolises primary to secondary bile acids, a process if disrupted by antibiotics, may be critical for the initiation of CDI. Aim: To assess the levels of primary and secondary bile acids associated with CDI and associated microbial changes. Methods: Stool and serum were collected from patients with (i) first CDI (fCDI), (ii) recurrent CDI (rCDI) and (iii) healthy controls. 16S rRNA sequencing and bile salt metabolomics were performed. Random forest regression models were constructed to predict disease status. PICRUSt analyses were used to test for associations between predicted bacterial bile salt hydrolase (BSH) gene abundances and bile acid levels. Results: Sixty patients (20 fCDI, 19 rCDI and 21 controls) were enrolled. Secondary bile acids in stool were significantly elevated in controls compared to rCDI and fCDI (P < 0.0001 and P = 0.0007 respectively). Primary bile acids in stool were significantly elevated in rCDI compared to controls (P < 0.0001) and in rCDI compared to fCDI (P = 0.02). Using random forest regression, we distinguished rCDI and fCDI patients 84.2% of the time using bile acid ratios. Stool deoxycholate to glycoursodeoxycholate ratio was the single best predictor. PICRUSt analyses found significant differences in predicted abundances of bacterial BSH genes in stool samples across the groups. Conclusions: Primary and secondary bile acid composition in stool was different in those with rCDI, fCDI and controls. The ratio of stool deoxycholate to glycoursodeoxycholate was the single best predictor of disease state and may be a potential biomarker for recurrence.American College of Gastroenterology (Clinical Research Award ACGJR-017-2015

Cell-State-Specific Metabolic Dependency in Hematopoiesis and Leukemogenesis

The balance between oxidative and non-oxidative glucose metabolism is essential for a number of pathophysiological processes. By deleting enzymes that affect aerobic glycolysis with different potencies, we examine how modulating glucose metabolism specifically affects hematopoietic and leukemic cell populations. We find that deficiency in the M2 pyruvate kinase isoform (PKM2) reduces levels of metabolic intermediates important for biosynthesis and impairs progenitor function without perturbing hematopoietic stem cells (HSC), whereas lactate dehydrogenase-A (LDHA) deletion significantly inhibits the function of both HSC and progenitors during hematopoiesis. In contrast, leukemia initiation by transforming alleles putatively affecting either HSC or progenitors is inhibited in the absence of either PKM2 or LDHA, indicating that the cell state-specific responses to metabolic manipulation in hematopoiesis do not apply to the setting of leukemia. This finding suggests that fine-tuning the level of glycolysis may be therapeutically explored for treating leukemia while preserving HSC function.National Institutes of Health (U.S.) (Grants P30CA147882 and R01CA168653)Smith Family FoundationBurroughs Wellcome FundVirginia and D.K. Ludwig Fund for Cancer ResearchDamon Runyon Cancer Research Foundatio

Metabolite Profiles During Oral Glucose Challenge

To identify distinct biological pathways of glucose metabolism, we conducted a systematic evaluation of biochemical changes after an oral glucose tolerance test (OGTT) in a community-based population. Metabolic profiling was performed on 377 nondiabetic Framingham Offspring cohort participants (mean age 57 years, 42% women, BMI 30 kg/m2) before and after OGTT. Changes in metabolite levels were evaluated with paired Student t tests, cluster-based analyses, and multivariable linear regression to examine differences associated with insulin resistance. Of 110 metabolites tested, 91 significantly changed with OGTT (P ≤ 0.0005 for all). Amino acids, β-hydroxybutyrate, and tricarboxylic acid cycle intermediates decreased after OGTT, and glycolysis products increased, consistent with physiological insulin actions. Other pathways affected by OGTT included decreases in serotonin derivatives, urea cycle metabolites, and B vitamins. We also observed an increase in conjugated, and a decrease in unconjugated, bile acids. Changes in β-hydroxybutyrate, isoleucine, lactate, and pyridoxate were blunted in those with insulin resistance. Our findings demonstrate changes in 91 metabolites representing distinct biological pathways that are perturbed in response to an OGTT. We also identify metabolite responses that distinguish individuals with and without insulin resistance. These findings suggest that unique metabolic phenotypes can be unmasked by OGTT in the prediabetic state

Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements

The immense and growing repositories of transcriptional data may contain critical insights for developing new therapies. Current approaches to mining these data largely rely on binary classifications of disease vs. control, and are not able to incorporate measures of disease severity. We report an analytical approach to integrate ordinal clinical information with transcriptomics. We apply this method to public data for a large cohort of Huntington's disease patients and controls, identifying and prioritizing phenotype-associated genes. We verify the role of a high-ranked gene in dysregulation of sphingolipid metabolism in the disease and demonstrate that inhibiting the enzyme, sphingosine-1-phosphate lyase 1 (SPL), has neuroprotective effects in Huntington's disease models. Finally, we show that one consequence of inhibiting SPL is intracellular inhibition of histone deacetylases, thus linking our observations in sphingolipid metabolism to a well-characterized Huntington's disease pathway. Our approach is easily applied to any data with ordinal clinical measurements, and may deepen our understanding of disease processes

Metabolites related to purine catabolism and risk of type 2 diabetes incidence; modifying efects of the TCF7L2-rs7903146 polymorphism

Studies examining associations between purine metabolites and type 2 diabetes (T2D) are limited. We prospectively examined associations between plasma levels of purine metabolites with T2D risk and the modifying effects of transcription factor-7-like-2 (TCF7L2) rs7903146 polymorphism on these associations. This is a case-cohort design study within the PREDIMED study, with 251 incident T2D cases and a random sample of 694 participants (641 non-cases and 53 overlapping cases) without T2D at baseline (median follow-up: 3.8 years). Metabolites were semi-quantitatively profiled with LC-MS/MS. Cox regression analysis revealed that high plasma allantoin levels, including allantoin-to-uric acid ratio and high xanthine-to-hypoxanthine ratio were inversely and positively associated with T2D risk, respectively, independently of classical risk factors. Elevated plasma xanthine and inosine levels were associated with a higher T2D risk in homozygous carriers of the TCF7L2-rs7903146 T-allele. The potential mechanisms linking the aforementioned purine metabolites and T2D risk must be also further investigated

Lysine pathway metabolites and the risk of type 2 diabetes and cardiovascular disease in the PREDIMED study: results from two case-cohort studies

Background: The pandemic of cardiovascular disease (CVD) and type 2 diabetes (T2D) requires the identifcation of new predictor biomarkers. Biomarkers potentially modifable with lifestyle changes deserve a special interest. Our aims were to analyze: (a) The associations of lysine, 2-aminoadipic acid (2-AAA) or pipecolic acid with the risk of T2D or CVD in the PREDIMED trial; (b) the efect of the dietary intervention on 1-year changes in these metabolites, and (c) whether the Mediterranean diet (MedDiet) interventions can modify the efects of these metabolites on CVD or T2D risk. Methods: Two unstratifed case-cohort studies nested within the PREDIMED trial were used. For CVD analyses, we selected 696 non-cases and 221 incident CVD cases; for T2D, we included 610 non-cases and 243 type 2 diabetes incident cases. Metabolites were quantifed using liquid chromatography–tandem mass spectrometry, at baseline and after 1-year of intervention. Results: In weighted Cox regression models, we found that baseline lysine (HR+1 SD increase=1.26; 95% CI 1.06–1.51) and 2-AAA (HR+1 SD increase=1.28; 95% CI 1.05–1.55) were both associated with a higher risk of T2D, but not with CVD. A signifcant interaction (p=0.032) between baseline lysine and T2D on the risk of CVD was observed: subjects with prevalent T2D and high levels of lysine exhibited the highest risk of CVD. The intervention with MedDiet did not have a signifcant efect on 1-year changes of the metabolites. Conclusions: Our results provide an independent prospective replication of the association of 2-AAA with future risk of T2D. We show an association of lysine with subsequent CVD risk, which is apparently diabetes-dependent. No evidence of efects of MedDiet intervention on lysine, 2-AAA or pipecolic acid changes was found

Arginine catabolism metabolites and atrial fibrillation or heart failure risk: 2 case-control studies within the Prevención con Dieta Mediterránea (PREDIMED) trial

Background Arginine-derived metabolites are involved in oxidative and inflammatory processes related to endothelial functions and cardiovascular risks. Objectives We prospectively examined the associations of arginine catabolism metabolites with the risks of atrial fibrillation (AF) or heart failure (HF), and evaluated the potential modifications of these associations through Mediterranean diet (MedDiet) interventions in a large, primary-prevention trial. Methods Two nested, matched, case-control studies were designed within the Prevención con Dieta Mediterránea (PREDIMED) trial. We selected 509 incident cases and 547 matched controls for the AF case-control study and 326 cases and 402 matched controls for the HF case-control study using incidence density sampling. Fasting blood samples were collected at baseline and arginine catabolism metabolites were measured using LC-tandem MS. Multivariable conditional logistic regression models were applied to test the associations between the metabolites and incident AF or HF. Interactions between metabolites and intervention groups (MedDiet groups compared with control group) were analyzed with the likelihood ratio test. Results Inverse association with incident AF was observed for arginine (OR per 1 SD, 0.83; 95% CI: 0.73–0.94), whereas a positive association was found for N1-acetylspermidine (OR for Q4 compared with Q1 1.58; 95% CI: 1.13–2.25). For HF, inverse associations were found for arginine (OR per 1 SD, 0.82; 95% CI: 0.69–0.97) and homoarginine (OR per 1 SD, 0.81; 95% CI: 0.68–0.96), and positive associations were found for the asymmetric dimethylarginine (ADMA) and symmetric dimethlyarginine (SDMA) ratio (OR per 1 SD, 1.19; 95% CI: 1.02–1.41), N1-acetylspermidine (OR per 1 SD, 1.34; 95% CI: 1.12–1.60), and diacetylspermine (OR per 1 SD, 1.20; 95% CI: 1.02–1.41). In the stratified analysis according to the dietary intervention, the lower HF risk associated with arginine was restricted to participants in the MedDiet groups (P-interaction = 0.044). Conclusions Our results suggest that arginine catabolism metabolites could be involved in AF and HF. Interventions with the MedDiet may contribute to strengthen the inverse association between arginine and the risk of HF. This trial was registered at controlled-trials.com as ISRCTN35739639

Circulating citric acid cycle metabolites and risk of cardiovascular disease in the PREDIMED study

Background and aim Plasma citric acid cycle (CAC) metabolites might be likely related to cardiovascular disease (CVD). However, studies assessing the longitudinal associations between circulating CAC-related metabolites and CVD risk are lacking. The aim of this study was to evaluate the association of baseline and 1-year levels of plasma CAC-related metabolites with CVD incidence (a composite of myocardial infarction, stroke or cardiovascular death), and their interaction with Mediterranean diet interventions. Methods and results Case-cohort study from the PREDIMED trial involving participants aged 55–80 years at high cardiovascular risk, allocated to MedDiets or control diet. A subcohort of 791 participants was selected at baseline, and a total of 231 cases were identified after a median follow-up of 4.8 years. Nine plasma CAC-related metabolites (pyruvate, lactate, citrate, aconitate, isocitrate, 2-hydroxyglutarate, fumarate, malate and succinate) were measured using liquid chromatography-tandem mass spectrometry. Weighted Cox multiple regression was used to calculate hazard ratios (HRs). Baseline fasting plasma levels of 3 metabolites were associated with higher CVD risk, with HRs (for each standard deviation, 1-SD) of 1.46 (95%CI:1.20–1.78) for 2-hydroxyglutarate, 1.33 (95%CI:1.12–1.58) for fumarate and 1.47 (95%CI:1.21–1.78) for malate (p of linear trend <0.001 for all). A higher risk of CVD was also found for a 1-SD increment of a combined score of these 3 metabolites (HR = 1.60; 95%CI: 1.32–1.94, p trend <0.001). This result was replicated using plasma measurements after one-year. No interactions were detected with the nutritional intervention. Conclusion Plasma 2-hydroxyglutarate, fumarate and malate levels were prospectively associated with increased cardiovascular risk

Plasma lipidome and risk of atrial fibrillation: results from the PREDIMED trial

The potential role of the lipidome in atrial fibrillation (AF) development is still widely unknown. We aimed to assess the association between lipidome profiles of the Prevención con Dieta Mediterránea (PREDIMED) trial participants and incidence of AF. We conducted a nested case-control study (512 incident centrally adjudicated AF cases and 735 controls matched by age, sex, and center). Baseline plasma lipids were profiled using a Nexera X2 U-HPLC system coupled to an Exactive Plus orbitrap mass spectrometer. We estimated the association between 216 individual lipids and AF using multivariable conditional logistic regression and adjusted the p values for multiple testing. We also examined the joint association of lipid clusters with AF incidence. Hitherto, we estimated the lipidomics network, used machine learning to select important network-clusters and AF-predictive lipid patterns, and summarized the joint association of these lipid patterns weighted scores. Finally, we addressed the possible interaction by the randomized dietary intervention.Forty-one individual lipids were associated with AF at the nominal level (p < 0.05), but no longer after adjustment for multiple-testing. However, the network-based score identified with a robust data-driven lipid network showed a multivariable-adjusted ORper+1SD of 1.32 (95% confidence interval: 1.16-1.51; p < 0.001). The score included PC plasmalogens and PE plasmalogens, palmitoyl-EA, cholesterol, CE 16:0, PC 36:4;O, and TG 53:3. No interaction with the dietary intervention was found. A multilipid score, primarily made up of plasmalogens, was associated with an increased risk of AF. Future studies are needed to get further insights into the lipidome role on AF.Current Controlled Trials number, ISRCTN35739639

Metabolic determinants of cancer cell sensitivity to glucose limitation and biguanides

As the concentrations of highly consumed nutrients, particularly glucose, are generally lower in tumours than in normal tissues1,2, cancer cells must adapt their metabolism to the tumour microenvironment. A better understanding of these adaptations might reveal cancer cell liabilities that can be exploited for therapeutic benefit. Here, we developed a continuous flow culture apparatus (Nutrostat) for maintaining proliferating cells in low nutrient media for long periods of time and used it to undertake competitive proliferation assays on a pooled collection of barcoded cancer cell lines cultured in low glucose conditions. Sensitivity to low glucose varies amongst cell lines, and an RNAi screen pinpointed mitochondrial oxidative phosphorylation (OXPHOS) as the major pathway required for optimal proliferation in low glucose. We found that cell lines most sensitive to low glucose are defective in the upregulation of OXPHOS normally caused by glucose limitation as a result of either mtDNA mutations in Complex I genes or impaired glucose utilization. These defects predict sensitivity to biguanides, anti-diabetic drugs that inhibit OXPHOS3,4, when cancer cells are grown in low glucose or as tumour xenografts. Remarkably, the biguanide sensitivity of cancer cells with mtDNA mutations was reversed by ectopic expression of yeast NDI1, a ubiquinone oxidoreductase that allows bypass of Complex I function5. Thus, we conclude that mtDNA mutations and impaired glucose utilization are potential biomarkers for identifying tumours with increased sensitivity to OXPHOS inhibitors