Use of dicarboxylic acids in type 2 diabetes

A charge reversal approach for the sensitive quantification of dicarboxylic acids using Liquid chromatography-tandem mass spectrometry

Dicarboxylic acids (DCAs) are essential for intermediate metabolism and are implicated in multiple processes associated with various diseases. Several DCAs contribute to energy metabolism, impact mitochondrial function, and play a crucial role in body function. However, the low abundance of some DCAs in various body fluids makes their quantification particularly challenging. Therefore, an extremely sensitive method is required to determine DCA level fluctuations in biological samples in different diseases. We developed and optimized an LC-MS/MS method to quantify DCAs. We achieved charge reversal of the compounds from negative to positive ionization through chemical derivatization with dimethylaminophenacyl bromide (DmPABr) targeting the carboxyl group (R-COOH) under mild basic conditions. Derivatization enhanced sensitivity, mass fragmentation, and chromatographic separation for LC-tandem mass spectrometric quantification. The method was analytically optimized and demonstrated excellent linearity for individual DCAs (R2>0.99), as well as an exceptionally lower limit of detection (LLOD<266 fg) and lower limit of quantification (LLOQ<805 fg) for all DCAs. Furthermore, most derivatized DCAs were stable at room temperature and after ten repeated freeze-thaw cycles. After DCA extraction and quantification detection, we found differences in their distribution in plasma and urine. The rank order for DCAs in plasma is C4>C6>C7>C9>C5>C8>C22, whereas in the urine sample, the order is C4>C7>C6>C9>C5>C8>C10. For longer chains (C > 16), their proportions were >10x higher in plasma than in urine. Our optimized method using LC-MS/MS enables the quantification of DCAs with excellent sensitivity. The method will help in future studies investigating dicarboxylic acids' crucial role in health and biomarker discovery studies using targeted metabolomics.

Exploring the role of Yuxuebi tablet in neuropathic pain with the method of similarity research of drug pharmacological effects based on unsupervised machine learning

Introduction

Having multiple pharmacological effects is a characteristic of Traditional Chinese Medicine (TCM). Currently, there is a lack of suitable methods to explore and discover modern diseases suitable for TCM treatment using this characteristic. Unsupervised machine learning technology is an efficient strategy to predict the pharmacological activity of drugs. This study takes Yuxuebi Tablet (YXB) as the research object. Using the unsupervised machine learning technology of drug cell functional fingerprint similarity research, the potential pharmacological effects of YXB were discovered and verified.

Methods

LC-MS combined with the in vitro intestinal absorption method was used to identify components of YXB that could be absorbed by the intestinal tract of rats. Unsupervised learning hierarchical clustering was used to calculate the degree of similarity of cellular functional fingerprints between these components and 121 marketed Western drugs whose indications are diseases and symptoms that YXB is commonly used to treat. Then, based on the Library of Integrated Network-based Cellular Signatures database, pathway analysis was performed for selected Western drugs with high similarity in cellular functional fingerprints with the components of YXB to discover the potential pharmacological effects of YXB, which were validated by animal experiments.

Results

We identified 40 intestinally absorbed components of YXB. Through predictive studies, we found that they have pharmacological effects very similar to non-steroidal anti-inflammatory drugs (NSAIDs) and corticosteroids. In addition, we found that they have very similar pharmacological effects to anti-neuropathic pain medications (such as gabapentin, duloxetine, and pethidine) and may inhibit the NF-κB signaling pathway and biological processes related to pain perception. Therefore, YXB may have an antinociceptive effect on neuropathic pain. Finally, we demonstrated that YXB significantly reduced neuropathic pain in a rat model of sciatic nerve chronic constriction injury (CCI). Transcriptome analysis further revealed that YXB regulates the expression of multiple genes involved in nerve injury repair, signal transduction, ion channels, and inflammatory response, with key regulatory targets including Sgk1, Sst, Isl1, and Shh.

Conclusion

This study successfully identified and confirmed the previously unknown pharmacological activity of YXB against neuropathic pain through unsupervised learning prediction and experimental verification.

Dicarboxylic acids counteract the metabolic effects of a Western diet by boosting energy expenditure

Obesity has reached pandemic proportion not only in the West but also in other countries around the world; it is now one of the leading causes of death worldwide. A Western diet is rich in saturated fats and provides more calories than necessary, contributing to the rise of the obesity rate. It also promotes the development of liver steatosis, insulin resistance, hyperglycemia, and hyperlipidemia. In this issue of the JCI, Goetzman and colleagues describe the effects of consuming dicarboxylic acids (DAs) as an alternative source of dietary fat. The 12-carbon dicarboxylic acid (DC12) was administered to mice at 20% of their daily caloric intake for nine weeks in place of triglycerides. Notably, the change in diet increased the metabolic rate, reduced body fat, reduced liver fat, and improved glucose tolerance. These findings highlight DAs as useful energy nutrients for combatting obesity and treating various metabolic disorders.

Sebacic Acid as a Potential Age-Related Biomarker of Liver Aging: Evidence Linking Mice and Human

The aging process is complicated and involves diverse organ dysfunction; furthermore, the biomarkers that are able to reflect biological aging are eagerly sought after to monitor the system-wide decline associated with the aging process. To address this, we performed a metabolomics analysis using a longitudinal cohort study from Taiwan (N = 710) and established plasma metabolomic age using a machine learning algorithm. The resulting estimation of age acceleration among the older adults was found to be correlated with HOMA-insulin resistance. In addition, a sliding window analysis was used to investigate the undulating decrease in hexanoic and heptanoic acids that occurs among the older adults at different ages. A comparison of the metabolomic alterations associated with aging between humans and mice implied that ω-oxidation of medium-chain fatty acids was commonly dysregulated in older subjects. Among these fatty acids, sebacic acid, an ω-oxidation product produced by the liver, was significantly decreased in the plasma of both older humans and aged mice. Notably, an increase in the production and consumption of sebacic acid within the liver tissue of aged mice was observed, along with an elevation of pyruvate-to-lactate conversion. Taken together, our study reveals that sebacic acid and metabolites of ω-oxidation are the common aging biomarkers in both humans and mice. The further analysis suggests that sebacic acid may play an energetic role in supporting the production of acetyl-CoA during liver aging, and thus its alteration in plasma concentration potentially reflects the aging process.

Predicting weight loss success on a new Nordic diet: an untargeted multi-platform metabolomics and machine learning approach

Background and aim

Results from randomized controlled trials indicate that no single diet performs better than other for all people living with obesity. Regardless of the diet plan, there is always large inter-individual variability in weight changes, with some individuals losing weight and some not losing or even gaining weight. This raises the possibility that, for different individuals, the optimal diet for successful weight loss may differ. The current study utilized machine learning to build a predictive model for successful weight loss in subjects with overweight or obesity on a New Nordic Diet (NND).

Methods

Ninety-one subjects consumed an NND ad libitum for 26 weeks. Based on their weight loss, individuals were classified as responders (weight loss ≥5%, n = 46) or non-responders (weight loss <2%, n = 24). We used clinical baseline data combined with baseline urine and plasma untargeted metabolomics data from two different analytical platforms, resulting in a data set including 2,766 features, and employed symbolic regression (QLattice) to develop a predictive model for weight loss success.

Results

There were no differences in clinical parameters at baseline between responders and non-responders, except age (47 ± 13 vs. 39 ± 11 years, respectively, p = 0.009). The final predictive model for weight loss contained adipic acid and argininic acid from urine (both metabolites were found at lower levels in responders) and generalized from the training (AUC 0.88) to the test set (AUC 0.81). Responders were also able to maintain a weight loss of 4.3% in a 12 month follow-up period.

Conclusion

We identified a model containing two metabolites that were able to predict the likelihood of achieving a clinically significant weight loss on an ad libitum NND. This work demonstrates that models based on an untargeted multi-platform metabolomics approach can be used to optimize precision dietary treatment for obesity.

Metabolome Alterations Linking Sugar-Sweetened Beverage Intake with Dyslipidemia in Youth: The Exploring Perinatal Outcomes among CHildren (EPOCH) Study

The objective of this study was to assess intermediary metabolic alterations that link sugar-sweetened beverage (SSB) intake to cardiometabolic (CM) risk factors in youth. A total of 597 participants from the multi-ethnic, longitudinal Exploring Perinatal Outcomes among CHildren (EPOCH) Study were followed in childhood (median 10 yrs) and adolescence (median 16 yrs). We used a multi-step approach: first, mixed models were used to examine the associations of SSB intake in childhood with CM measures across childhood and adolescence, which revealed a positive association between SSB intake and fasting triglycerides (β (95% CI) for the highest vs. lowest SSB quartile: 8.1 (−0.9,17.0); p-trend = 0.057). Second, least absolute shrinkage and selection operator (LASSO) regression was used to select 180 metabolite features (out of 767 features assessed by untargeted metabolomics) that were associated with SSB intake in childhood. Finally, 13 of these SSB-associated metabolites (from step two) were also prospectively associated with triglycerides across follow-up (from step one) in the same direction as with SSB intake (Bonferroni-adj. p < 0.0003). All annotated compounds were lipids, particularly dicarboxylated fatty acids, mono- and diacylglycerols, and phospholipids. In this diverse cohort, we identified a panel of lipid metabolites that may serve as intermediary biomarkers, linking SSB intake to dyslipidemia risk in youth.

Transcriptome-wide association study for postpartum depression implicates altered B-cell activation and insulin resistance

Postpartum depression (PPD) affects 1 in 7 women and has negative mental health consequences for both mother and child. However, the precise biological mechanisms behind the disorder are unknown. Therefore, we performed the largest transcriptome-wide association study (TWAS) for PPD (482 cases, 859 controls) to date using RNA-sequencing in whole blood and deconvoluted cell types. No transcriptional changes were observed in whole blood. B-cells showed a majority of transcriptome-wide significant results (891 transcripts representing 789 genes) with pathway analyses implicating altered B-cell activation and insulin resistance. Integration of other data types revealed cell type-specific DNA methylation loci and disease-associated eQTLs (deQTLs), but not hormones/neuropeptides (estradiol, progesterone, oxytocin, BDNF), serve as regulators for part of the transcriptional differences between cases and controls. Further, deQTLs were enriched for several brain region-specific eQTLs, but no overlap with MDD risk loci was observed. Altogether, our results constitute a convergence of evidence for pathways most affected in PPD with data across different biological mechanisms.

Distinct Serum and Fecal Metabolite Profiles Linking With Gut Microbiome in Older Adults With Frailty

Frailty is a critical aging-related syndrome but the underlying metabolic mechanism remains poorly understood. The aim of this study was to identify novel biomarkers and reveal potential mechanisms of frailty based on the integrated analysis of metabolome and gut microbiome. In this study, twenty subjects consisted of five middle-aged adults and fifteen older adults, of which fifteen older subjects were divided into three groups: non-frail, pre-frail, and frail, with five subjects in each group. The presence of frailty, pre-frailty, or non-frailty was established according to the physical frailty phenotype (PFP). We applied non-targeted metabolomics to serum and feces samples and used 16S rDNA gene sequencing to detect the fecal microbiome. The associations between metabolites and gut microbiota were analyzed by the Spearman’s correlation analysis. Serum metabolic shifts in frailty mainly included fatty acids and derivatives, carbohydrates, and monosaccharides. Most of the metabolites belonging to these classes increased in the serum of frail older adults. Propylparaben was found to gradually decrease in non-frail, pre-frail, and frail older adults. Distinct changes in fecal metabolite profiles and gut microbiota were also found among middle-aged adults, non-frail and frail older subjects. The relative abundance of Faecalibacteriu, Roseburia, and Fusicatenibacter decreased while the abundance of Parabacteroides and Bacteroides increased in frailty. The above altered microbes were associated with the changed serum metabolites in frailty, which included dodecanedioic acid, D-ribose, D-(-)-mannitol, creatine and indole, and their related fecal metabolites. The changed microbiome and related metabolites may be used as the biomarkers of frailty and is worthy of further mechanistic studies.

Serum Metabolites Associated with Blood Pressure in Chronic Kidney Disease Patients

Blood pressure is one of the most basic health screenings and it has a complex relationship with chronic kidney disease (CKD). Controlling blood pressure for CKD patients is crucial for curbing kidney function decline and reducing the risk of cardiovascular disease. Two independent CKD cohorts, including matched controls (discovery n = 824; validation n = 552), were recruited. High-throughput metabolomics was conducted with the patients’ serum samples using mass spectrometry. After controlling for CKD severity and other clinical hypertension risk factors, we identified ten metabolites that have significant associations with blood pressure. The quantitative importance of these metabolites was verified in a fully connected neural network model. Of the ten metabolites, seven have not previously been associated with blood pressure. The metabolites that had the strongest positive association with blood pressure were aspartylglycosamine (p = 4.58 × 10−5), fructose-1,6-diphosphate (p = 1.19 × 10−4) and N-Acetylserine (p = 3.27 × 10−4). Three metabolites that were negatively associated with blood pressure (phosphocreatine, p = 6.39 × 10−3; dodecanedioic acid, p = 0.01; phosphate, p = 0.04) have been reported previously to have beneficial effects on hypertension. These results suggest that intake of metabolites as supplements may help to control blood pressure in CKD patients.

A meta-analysis study of the robustness and universality of gut microbiome-metabolome associations

BACKGROUND

Microbiome-metabolome studies of the human gut have been gaining popularity in recent years, mostly due to accumulating evidence of the interplay between gut microbes, metabolites, and host health. Statistical and machine learning-based methods have been widely applied to analyze such paired microbiome-metabolome data, in the hope of identifying metabolites that are governed by the composition of the microbiome. Such metabolites can be likely modulated by microbiome-based interventions, offering a route for promoting gut metabolic health. Yet, to date, it remains unclear whether findings of microbially associated metabolites in any single study carry over to other studies or cohorts, and how robust and universal are microbiome-metabolites links.

RESULTS

In this study, we addressed this challenge by performing a comprehensive meta-analysis to identify human gut metabolites that can be predicted based on the composition of the gut microbiome across multiple studies. We term such metabolites "robustly well-predicted". To this end, we processed data from 1733 samples from 10 independent human gut microbiome-metabolome studies, focusing initially on healthy subjects, and implemented a machine learning pipeline to predict metabolite levels in each dataset based on the composition of the microbiome. Comparing the predictability of each metabolite across datasets, we found 97 robustly well-predicted metabolites. These include metabolites involved in important microbial pathways such as bile acid transformations and polyamines metabolism. Importantly, however, other metabolites exhibited large variation in predictability across datasets, suggesting a cohort- or study-specific relationship between the microbiome and the metabolite. Comparing taxonomic contributors to different models, we found that some robustly well-predicted metabolites were predicted by markedly different sets of taxa across datasets, suggesting that some microbially associated metabolites may be governed by different members of the microbiome in different cohorts. We finally examined whether models trained on a control group of a given study successfully predicted the metabolite's level in the disease group of the same study, identifying several metabolites where the model was not transferable, indicating a shift in microbial metabolism in disease-associated dysbiosis.

CONCLUSIONS

Combined, our findings provide a better understanding of the link between the microbiome and metabolites and allow researchers to put identified microbially associated metabolites within the context of other studies. Video abstract.

Metabolic Outcomes of Anaplerotic Dodecanedioic Acid Supplementation in Very Long Chain Acyl-CoA Dehydrogenase (VLCAD) Deficient Fibroblasts

Very long-chain acyl-CoA dehydrogenase deficiency (VLCADD, OMIM 609575) is associated with energy deficiency and mitochondrial dysfunction and may lead to rhabdomyolysis and cardiomyopathy. Under physiological conditions, there is a fine balance between the utilization of different carbon nutrients to maintain the Krebs cycle. The maintenance of steady pools of Krebs cycle intermediates is critical formitochondrial energy homeostasis especially in high-energy demanding organs such as muscle and heart. Even-chain dicarboxylic acids are established as alternative energy carbon sources that replenish the Krebs cycle by bypassing a defective β-oxidation pathway. Despite this, even-chain dicarboxylic acids are eliminated in the urine of VLCAD-affected individuals. In this study, we explore dodecanedioic acid (C12; DODA) supplementation and investigate its metabolic effect on Krebs cycle intermediates, glucose uptake, and acylcarnitine profiles in VLCAD-deficient fibroblasts. Our findings indicate that DODA supplementation replenishes the Krebs cycle by increasing the succinate pool, attenuates glycolytic flux, and reduces levels of toxic very long-chain acylcarnitines.

Circulating short and medium chain fatty acids are associated with normoalbuminuria in type 1 diabetes of long duration

A substantial number of subjects with Type 1 Diabetes (T1D) of long duration never develop albuminuria or renal function impairment, yet the underlying protective mechanisms remain unknown. Therefore, our study included 308 Joslin Kidney Study subjects who had T1D of long duration (median: 24 years), maintained normal renal function and had either normoalbuminuria or a broad range of albuminuria within the 2 years preceding the metabolomic determinations. Serum samples were subjected to global metabolomic profiling. 352 metabolites were detected in at least 80% of the study population. In the logistic analyses adjusted for multiple testing (Bonferroni corrected α = 0.000028), we identified 38 metabolites associated with persistent normoalbuminuria independently from clinical covariates. Protective metabolites were enriched in Medium Chain Fatty Acids (MCFAs) and in Short Chain Fatty Acids (SCFAs) and particularly involved odd-numbered and dicarboxylate Fatty Acids. One quartile change of nonanoate, the top protective MCFA, was associated with high odds of having persistent normoalbuminuria (OR (95% CI) 0.14 (0.09, 0.23); p < 10-12). Multivariable Random Forest analysis concordantly indicated to MCFAs as effective classifiers. Associations of the relevant Fatty Acids with albuminuria seemed to parallel associations with tubular biomarkers. Our findings suggest that MCFAs and SCFAs contribute to the metabolic processes underlying protection against albuminuria development in T1D that are independent from mechanisms associated with changes in renal function.

Disease-associated gut microbiome and metabolome changes in patients with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is the third commonest cause of death globally, and manifests as a progressive inflammatory lung disease with no curative treatment. The lung microbiome contributes to COPD progression, but the function of the gut microbiome remains unclear. Here we examine the faecal microbiome and metabolome of COPD patients and healthy controls, finding 146 bacterial species differing between the two groups. Several species, including Streptococcus sp000187445, Streptococcus vestibularis and multiple members of the family Lachnospiraceae, also correlate with reduced lung function. Untargeted metabolomics identifies a COPD signature comprising 46% lipid, 20% xenobiotic and 20% amino acid related metabolites. Furthermore, we describe a disease-associated network connecting Streptococcus parasanguinis_B with COPD-associated metabolites, including N-acetylglutamate and its analogue N-carbamoylglutamate. While correlative, our results suggest that the faecal microbiome and metabolome of COPD patients are distinct from those of healthy individuals, and may thus aid in the search for biomarkers for COPD.

Chronic obstructive pulmonary disease (COPD) is a progressing disease, with lung but not gut microbiota implicated in its etiology. Here the authors compare the stool from patients with COPD and healthy controls to find specific gut bacteria and metabolites associated with active disease, thereby hinting at a potential role for the gut microbiome in COPD.

Analysis of biomarkers and metabolic pathways in patients with unstable angina based on ultra‑high‑performance liquid chromatography‑quadrupole time‑of‑flight mass spectrometry

Unstable angina (UA) is a coronary disease with a high mortality and morbidity worldwide. The present study aimed to use non-invasive techniques to identify urine biomarkers in patients with UA, so as to provide more information for the early diagnosis and treatment of the disease. Based on metabolomics, urine samples from 28 patients with UA and 28 healthy controls (HCs) were analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). A total of 16 significant biomarkers that could distinguish between patients with UA and HCs, including D-glucuronic acid, creatinine, succinic acid and N-acetylneuraminic acid, were identified. The major metabolic pathways associated with UA were subsequently analyzed by non-targeted metabolomics. The results demonstrated that amino acid and energy metabolism, fatty acid metabolism, purine metabolism and steroid hormone biosynthetic metabolism may serve important roles in UA. The results of the current study may provide a theoretical basis for the early diagnosis of UA and novel treatment strategies for clinicians. The trial was registered with the Chinese Clinical Trial Registration Center (registration no. ChiCTR-ROC-17013957) at Tianjin University of Traditional Chinese Medicine.

Type 2 Diabetes Metabolic Improvement After Roux-en-Y Gastric Bypass May Include a Compensatory Mechanism That Balances Fatty Acid β and ω Oxidation

BACKGROUND

More than half of patients who undergo Roux-en-Y gastric bypass (RYGB) can experience type 2 diabetes (T2D) remission, but the systemic and gastrointestinal (GI) metabolic mechanisms of this improvement are still elusive.

METHODS

Paired samples collected before and 3 months after RYGB from 28 women with obesity and T2D were analyzed by metabolomics with gas chromatography coupled to mass spectrometry. Samples include plasma (n = 56) and biopsies of gastric pouch (n = 18), gastric remnant (n = 10), duodenum (n = 16), jejunum (n = 18), and ileum (n = 18), collected by double-balloon enteroscopy.

RESULTS

After RYGB, improvements in body composition and weight-related and glucose homeostasis parameters were observed. Plasma-enriched metabolic pathways included arginine and proline metabolism, urea and tricarboxylic acid (TCA) cycles, gluconeogenesis, malate-aspartate shuttle, and carnitine synthesis. In GI tissue, we observed alterations of ammonia recycling and carnitine synthesis in gastric pouch, phenylacetate metabolism and trehalose degradation in duodenum and jejunum, ketone bodies in jejunum, and lactose degradation in ileum. Intermediates molecules of the TCA cycle were enriched, particularly in plasma, jejunum, and ileum. Fluctuations of dicarboxylic acids (DCAs) were relevant in several metabolomic tests, and metabolite alterations included aminomalonate and fumaric, malic, oxalic, and succinic acids. The product/substrate relationship between these molecules and its pathways may reflect a compensatory mechanism to balance metabolism.

CONCLUSIONS

RYGB was associated with systemic and GI metabolic reprogramming. DCA alterations link ω and β fatty acid oxidation to homeostatic mechanisms, including TCA cycle improvement.

The mitochondrial-derived peptide MOTS-c is a regulator of plasma metabolites and enhances insulin sensitivity

MOTS‐c is an exercise mimetic and improves insulin sensitivity in aged and diet‐induced obese mice. Although plasma markers are good markers for the metabolic condition, whether MOTS‐c changes plasma markers in diet‐induced obese mice has not been examined. Here, we used an unbiased metabolomics approach to examine the effect of MOTS‐c on plasma markers of metabolic dysfunction. We found that three pathways – sphingolipid metabolism, monoacylglycerol metabolism, and dicarboxylate metabolism – were reduced in MOTS‐c–injected mice. Interestingly, these pathways are upregulated in obese and T2D models. MOTS‐c improves insulin sensitivity and increases beta‐oxidation to prevent fat accumulation in DIO mice through these pathways. These results provide us a better understanding of the mechanism of how MOTS‐c improves insulin sensitivity and reduces the body weight and fatty liver and opens a new venue for further study.

Role of mitochondrial acyl-CoA dehydrogenases in the metabolism of dicarboxylic fatty acids

Dicarboxylic fatty acids, taken as a nutritional supplement or produced endogenously via omega oxidation of monocarboxylic fatty acids, may have therapeutic potential for rare inborn errors of metabolism as well as common metabolic diseases such as type 2 diabetes. Breakdown of dicarboxylic acids yields acetyl-CoA and succinyl-CoA as products, the latter of which is anaplerotic for the TCA cycle. However, little is known about the metabolic pathways responsible for degradation of dicarboxylic acids. Here, we demonstrated with whole-cell fatty acid oxidation assays that both mitochondria and peroxisomes contribute to dicarboxylic acid degradation. Several mitochondrial acyl-CoA dehydrogenases were tested for activity against dicarboxylyl-CoAs. Medium-chain acyl-CoA dehydrogenase (MCAD) exhibited activity with both six and 12 carbon dicarboxylyl-CoAs, and the capacity for dehydrogenation of these substrates was significantly reduced in MCAD knockout mouse liver. However, when dicarboxylic acids were fed to normal mice, the expression of MCAD did not change, while expression of peroxisomal fatty acid oxidation enzymes was greatly upregulated. In conclusion, mitochondrial fatty acid oxidation, and in particular MCAD, contributes to dicarboxylic acid degradation, but feeding dicarboxylic acids induces only the peroxisomal pathway.

Untargeted UPLC-MS metabolomics reveals multiple changes of urine composition in healthy adult volunteers after consumption of curcuma longa L. extract

Curcuma longa L. is used as food supplement to prevent diseases, although limited studies have been performed on healthy subjects up to now. In the present work, an untargeted UPLC-MS metabolomics approach was applied to study the changes of 24-hours urinary composition on healthy volunteers due to a 28-days daily consumption of a dried C. longa extract containing a standardized amount of curcuminoids. Changes in the excretion of different metabolites were observed after supplementation. Curcumin and two metabolic derivatives (hexahydrocurcumin and dihydrocurcumin) were detected in urine, indicating the absorption of the main curcuminoid from the extract and its further metabolism by liver and gut microbiota. For the first time ar-turmerone, the main apolar constituent of curcuma, was detected in urine in intact form, and its presence was confirmed by a targeted GC-MS analysis. The increase of tetranor-PGJM and tetranor-PGDM, two prostaglandin-D2 metabolites, was observed, being related to the anti-inflammatory effect exerted by curcuma. The variation of the amounts of HPAG, PAG, proline-betaine and hydroxyphenyllactic acid indicate that the supplementation induced changes to the activity of gut microbiota. Finally, the reduced excretion of niacin metabolites (nicotinuric acid, trigonelline and 2PY) and medium- and short-chain acylcarnitines suggests that curcuma could induce the mitochondrial β-oxidation of fatty acids for energy production in healthy subjects. Overall, the results indicate that a prolonged daily consumption of a dried curcuma extract exerts multiple effects on healthy subjects, furthermore they show the opportunity offered by untargeted metabolomics for the study of the bioactivity of natural extracts in healthy human volunteers.

The metabolomic signature of extreme longevity: naked mole rats versus mice

The naked mole-rat (Heterocephalus glaber) is characterized by a more than tenfold higher life expectancy compared to another rodent species of the same size, namely, the laboratory mouse (Mus musculus). We used mass spectrometric metabolomics to analyze circulating plasma metabolites in both species at different ages. Interspecies differences were much more pronounced than age-associated alterations in the metabolome. Such interspecies divergences affected multiple metabolic pathways involving amino, bile and fatty acids as well as monosaccharides and nucleotides. The most intriguing metabolites were those that had previously been linked to pro-health and antiaging effects in mice and that were significantly increased in the long-lived rodent compared to its short-lived counterpart. This pattern applies to α-tocopherol (also known as vitamin E) and polyamines (in particular cadaverine, N8-acetylspermidine and N1,N8-diacetylspermidine), all of which were more abundant in naked mole-rats than in mice. Moreover, the age-associated decline in spermidine and N1-acetylspermidine levels observed in mice did not occur, or is even reversed (in the case of N1-acetylspermidine) in naked mole-rats. In short, the present metabolomics analysis provides a series of testable hypotheses to explain the exceptional longevity of naked mole-rats.

Extending Classification Algorithms to Case-Control Studies

Classification is a common technique applied to 'omics data to build predictive models and identify potential markers of biomedical outcomes. Despite the prevalence of case-control studies, the number of classification methods available to analyze data generated by such studies is extremely limited. Conditional logistic regression is the most commonly used technique, but the associated modeling assumptions limit its ability to identify a large class of sufficiently complicated 'omic signatures. We propose a data preprocessing step which generalizes and makes any linear or nonlinear classification algorithm, even those typically not appropriate for matched design data, available to be used to model case-control data and identify relevant biomarkers in these study designs. We demonstrate on simulated case-control data that both the classification and variable selection accuracy of each method is improved after applying this processing step and that the proposed methods are comparable to or outperform existing variable selection methods. Finally, we demonstrate the impact of conditional classification algorithms on a large cohort study of children with islet autoimmunity.

Metabolomics signature associated with circulating serum selenoprotein P levels

PURPOSE

Selenoprotein P (SELENOP) has been previously related to various metabolic traits with partially conflicting results. The identification of SELENOP-associated metabolites, using an untargeted metabolomics approach, may provide novel biological insights relevant to disentangle the role of SELENOP in human health.

METHODS

In this cross-sectional study, 572 serum metabolites were identified by comparing the obtained LC-MS/MS spectra with spectra stored in Metabolon's spectra library. Serum SELENOP levels were measured in 832 men and women using an ELISA kit.

RESULTS

Circulating SELENOP levels were associated with 24 out of 572 metabolites after accounting for the number of independent dimensions in the metabolomics data, including inverse associations with alanine, glutamate, leucine, isoleucine and valine, an unknown compound X-12063, urate and the peptides gamma-glutamyl-leucine, and N-acetylcarnosine. Positive associations were observed between SELENOP and several lipid compounds. Of the identified metabolites, each standard deviation increase in the branched-chain amino acids (isoleucine, leucine, valine), alanine and gamma-glutamyl-leucine was related to higher odds of having T2DM [OR (95% CI): 1.96 (1.41-2.73); 1.62 (1.15-2.28); 1.94 (1.45-2.60), 1.57 (1.17-2.11), and 1.52 (1.13-2.05), respectively].

CONCLUSIONS

Higher serum SELENOP levels were associated with an overall healthy metabolomics profile, which may provide further insights into potential mechanisms of SELENOP-associated metabolic disorders.

Improving α, ω-dodecanedioic acid productivity from n-dodecane and hydrolysate of Candida cells by membrane integrated repeated batch fermentation

The aim of the present study is to develop an effective production process for α, ω-dodecanedioic acid (DC₁₂) biosynthesis using n-dodecane and hydrolysate of Candida cells as substrates by membrane integrated repeated batch fermentation. Cells and n-dodecane were simultaneously recycled during the filtration of fermentation broth (FB) with a 150 kDa ceramic membrane under a cross-flow velocity of 4 m/s and a trans-membrane pressure of 0.2 MPa, and it was also revealed that the cells in the broth could alleviate the membrane fouling during the FB filtration. Moreover, the hydrolysate of the collected cells could be successfully used as a nitrogen source to replace 50% yeast extract for decreasing the DC₁₂ production cost. With repeated-batch culture in a membrane bioreactor, the maximal DC₁₂ productivity could be enhanced by 57.8% compared with the batch culture, meanwhile n-dodecane and cells could be recovered and used for the next fermentation cycle.

Simultaneous decolorization and deproteinization of α,ω-dodecanedioic acid fermentation broth by integrated ultrafiltration and adsorption treatments

α,ω-Dicarboxylic acids (DC) are versatile chemical intermediates with different chain length. For biosynthesis of DC, to obtain the highly pure product via crystallization, it is required to remove pigments and proteins in fermentation broth. However, a trade-off between decolorization/deproteinization ratio and DC recovery during the purification process was found, which impeded DC production by fermentation. When ultrafiltration (UF) was applied to treat α,ω-dodecanedioic acid (DC₁₂) broth, 93.4% of DC₁₂ recovery, 80.5% of decolorization ratio and 61.7% of deproteinization ratio were achieved by a PES 3 membrane. However, the membrane technology could not effectively retain the pigments or proteins with low molecular weight when a high DC₁₂ permeation was required. Meanwhile, the selected activated charcoal or macroporous resins were not good adsorbents for the present system. Furthermore, an integrated process for decolorization and deproteinization was developed. After filtration with PES3 membrane, an activated charcoal was used to remove the small proteins and pigments in the UF permeate. As a result, 91.4% of DC₁₂ recovery, 94.7% of decolorization ratio and 84.8% of deproteinization ratio were obtained by such two-stage strategy. These results would serve as a valuable guide for process design and practical operation in subsequent industrial application.

α, ω-Dodecanedioic acid production by Candida viswanathii ipe-1 with co-utilization of wheat straw hydrolysates and n-dodecane

Candida viswanathii ipe-1 was used to produce α, ω-dodecanedioic acid (DC₁₂), which showed capability to ferment xylose and glucose simultaneously, while arabinose utilization was less efficient. A low concentration of furfural enhanced cell growth, and the addition of 4.0g/L sodium acetate largely increased DC₁₂ production. It indicated that detoxification of the wheat straw hydrolysates was not necessary for the biosynthesis of DC₁₂. Based on the promising features of our strain, an efficient process was developed to produce DC₁₂ from co-utilization of wheat straw hydrolysates and n-dodecane. Using this process, 129.7g/L DC₁₂ with a corresponding productivity of 1.13g·L^-1·h^-1 could be produced, which was increased by 40.0% compared with a sole carbon of glucose. The improved DC₁₂ yield by the co-utilization of wheat straw hydrolysates and n-dodecane using C. viswanathii ipe-1 demonstrates the great potential of using biomass as a feedstock in the production of DC₁₂.

Inter-relations between 3-hydroxypropionate and propionate metabolism in rat liver: relevance to disorders of propionyl-CoA metabolism

Propionate, 3-hydroxypropionate (3HP), methylcitrate, related compounds, and ammonium accumulate in body fluids of patients with disorders of propionyl-CoA metabolism, such as propionic acidemia. Although liver transplantation alleviates hyperammonemia, high concentrations of propionate, 3HP, and methylcitrate persist in body fluids. We hypothesized that conserved metabolic perturbations occurring in transplanted patients result from the simultaneous presence of propionate and 3HP in body fluids. We investigated the inter-relations of propionate and 3HP metabolism in perfused livers from normal rats using metabolomic and stable isotopic technologies. In the presence of propionate, 3HP, or both, we observed the following metabolic perturbations. First, the citric acid cycle (CAC) is overloaded but does not provide sufficient reducing equivalents to the respiratory chain to maintain the homeostasis of adenine nucleotides. Second, there is major CoA trapping in the propionyl-CoA pathway and a tripling of liver total CoA within 1 h. Third, liver proteolysis is stimulated. Fourth, propionate inhibits the conversion of 3HP to acetyl-CoA and its oxidation in the CAC. Fifth, some propionate and some 3HP are converted to nephrotoxic maleate by different processes. Our data have implications for the clinical management of propionic acidemia. They also emphasize the perturbations of the liver intermediary metabolism induced by supraphysiological, i.e., millimolar, concentrations of labeled propionate used to trace the intermediary metabolism, in particular, inhibition of CAC flux and major decreases in the [ATP]/[ADP] and [ATP]/[AMP] ratios.

High-level productivity of α,ω-dodecanedioic acid with a newly isolated Candida viswanathii strain

α,ω-Dicarboxylic acids (DC) are versatile chemical intermediates with different chain lengths, which are well-known as polymer building block. In this work, a new strain with high productivity of DC was isolated from oil-contaminated soil. Based on the morphology and phylogenetic analyses of the internal transcribed spacer sequences, it was characterized as Candida viswanathii. It was found that the contribution of carbon flux to the cell growth and DC production from n-dodecane could be regulated by the sucrose and yeast extract concentrations in the medium, and besides the broth pH, a suitable proportioning of sucrose and yeast extract was the key to achieve the optimal transition from cell growth phase to DC production phase. By optimizing culture conditions in a 7.5-L bioreactor, a higher DC productivity of 1.59 g·L−1 h−1 with a corresponding concentration of 181.6 g/L was obtained. After the purification of DC from the culture, the results from gas chromatography–mass spectrometry, infrared spectroscopy and 1H-NMR showed that α,ω-dodecanedioic acid (DC12) was the major product of C. viswanathii ipe-1 using pure n-dodecane as substrate. For the first time, we reported that a high productivity of DC12 could be produced by C. viswanathii.

Early Prediction of Developing Type 2 Diabetes by Plasma Acylcarnitines: A Population-Based Study

OBJECTIVE

Acylcarnitines were suggested as early biomarkers even prior to insulin resistance in animal studies, but their roles in predicting type 2 diabetes were unknown. Therefore, we aimed to determine whether acylcarnitines could independently predict type 2 diabetes by using a targeted metabolic profiling approach.

RESEARCH DESIGN AND METHODS

A population-based prospective study was conducted among 2,103 community-living Chinese individuals aged 50-70 years from Beijing and Shanghai with a mean follow-up duration of 6 years. Fasting glucose, glycohemoglobin, and insulin were determined at baseline and in a follow-up survey. Baseline plasma acylcarnitines were profiled by liquid chromatography-tandem mass spectrometry.

RESULTS

Over the 6-year period, 507 participants developed diabetes. A panel of acylcanitines, especially with long chain, was significantly associated with increased risk of type 2 diabetes. The relative risks of type 2 diabetes per SD increase of the predictive model score were 2.48 (95% CI 2.20-2.78) for the conventional and 9.41 (95% CI 7.62-11.62) for the full model including acylcarnitines, respectively. Moreover, adding selected acylcarnitines substantially improved predictive ability for incident diabetes, as area under the receiver operator characteristic curve improved to 0.89 in the full model compared with 0.73 in the conventional model. Similar associations were obtained when the predictive models were established separately among Beijing or Shanghai residents.

CONCLUSIONS

A panel of acylcarnitines, mainly involving mitochondrial lipid dysregulation, significantly improved predictive ability for type 2 diabetes beyond conventional risk factors. These findings need to be replicated in other populations, and the underlying mechanisms should be elucidated.

Localized delivery and enhanced osteogenic differentiation with biodegradable galactitol polyester elastomers

Cytocompatible galactitol based polyesters showed variations in physical properties, degradation, dye release and ability to direct cells towards bone lineage.

The anti-atherosclerotic effect of tanshinol borneol ester using fecal metabolomics based on liquid chromatography-mass spectrometry

Tanshinol borneol ester (DBZ) is a novel experimental compound that consists of two chemical structural units from danshensu and borneol. It exhibits efficacious anti-ischemic and anti-atherosclerosis activities in rats. A fecal metabolomics based on Liquid Chromatography-Mass Spectrometry combined with clinical histopathology and blood lipid estimation was employed to assess the efficacy and the metabolic changes caused by administration of DBZ in atherosclerotic rats. There were the typical pathological features of atherosclerosis and significantly increased levels of TC, TG and LDL-C in the atherosclerotic rat group. Nevertheless, atherosclerotic rats administered both DBZ (at a dose of 40 mg kg(-1)) and simvastatin (at a dose of 20 mg kg(-1)) showed good therapeutic effects. The results of the metabolomics studies showed that 55 differential metabolites such as sebacic acid, enterodiol, nonanedioic acid, dodecanedioic acid, cholic acid, 13(S)-HPODE, deoxycholic acid, some phosphatidylglycerol and phosphatidic acids were found, indicating that abnormal metabolism occurred in the pathways of fatty acid oxidation, linoleic acid metabolism, bile acid biosynthesis and glycerophospholipid metabolism in atherosclerotic rats. Compared to those in the model group, the contents of 41 differential metabolites showed a tendency to recover to a healthy level after DBZ administration. Metabolomics studies suggested that DBZ exhibited good treatment efficacy against atherosclerosis by adjusting disturbed metabolic pathways related to atherosclerosis. This study could provide an experimental basis for DBZ's application to act as a candidate drug with anti-atherosclerosis activity.

Compartmentation of Metabolism of the C12-, C9-, and C5-n-dicarboxylates in Rat Liver, Investigated by Mass Isotopomer Analysis: ANAPLEROSIS FROM DODECANEDIOATE

We investigated the compartmentation of the catabolism of dodecanedioate (DODA), azelate, and glutarate in perfused rat livers, using a combination of metabolomics and mass isotopomer analyses. Livers were perfused with recirculating or nonrecirculating buffer containing one fully (13)C-labeled dicarboxylate. Information on the peroxisomal versus mitochondrial catabolism was gathered from the labeling patterns of acetyl-CoA proxies, i.e. total acetyl-CoA, the acetyl moiety of citrate, C-1 + 2 of β-hydroxybutyrate, malonyl-CoA, and acetylcarnitine. Additional information was obtained from the labeling patterns of citric acid cycle intermediates and related compounds. The data characterize the partial oxidation of DODA and azelate in peroxisomes, with terminal oxidation in mitochondria. We did not find evidence of peroxisomal oxidation of glutarate. Unexpectedly, DODA contributes a substantial fraction to anaplerosis of the citric acid cycle. This opens the possibility to use water-soluble DODA in nutritional or pharmacological anaplerotic therapy when other anaplerotic substrates are impractical or contraindicated, e.g. in propionic acidemia and methylmalonic acidemia.

The peroxisomal enzyme L-PBE is required to prevent the dietary toxicity of medium-chain fatty acids

Specific metabolic pathways are activated by different nutrients to adapt the organism to available resources. Although essential, these mechanisms are incompletely defined. Here, we report that medium-chain fatty acids contained in coconut oil, a major source of dietary fat, induce the liver ω-oxidation genes Cyp4a10 and Cyp4a14 to increase the production of dicarboxylic fatty acids. Furthermore, these activate all ω- and β-oxidation pathways through peroxisome proliferator activated receptor (PPAR) α and PPARγ, an activation loop normally kept under control by dicarboxylic fatty acid degradation by the peroxisomal enzyme L-PBE. Indeed, L-pbe(-/-) mice fed coconut oil overaccumulate dicarboxylic fatty acids, which activate all fatty acid oxidation pathways and lead to liver inflammation, fibrosis, and death. Thus, the correct homeostasis of dicarboxylic fatty acids is a means to regulate the efficient utilization of ingested medium-chain fatty acids, and its deregulation exemplifies the intricate relationship between impaired metabolism and inflammation.