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Aim: To evaluate the association between single-nucleotide polymorphisms in the 3′ untranslated region of the DEFA5 gene and IgA nephropathy (IgAN) risk, the authors performed an association study in the Chinese Han population. Materials & methods: The authors recruited 426 IgAN patients and 498 controls. The MassARRAY platform (Agena Bioscience, Inc., CA, USA) was used to genotype single-nucleotide polymorphisms in DEFA5. Odds ratios and 95% CIs were calculated through logistic regression analysis. Results: The authors observed that rs12716641 significantly reduced IgAN risk in the allele (odds ratio: 0.77; p = 0.026) and genotype (odds ratio: 0.75; p = 0.039) models. Stratification analysis revealed that several genotypes of rs12716641 played a protective role against IgAN. Conclusion: The authors' results revealed that single-nucleotide polymorphisms in the 3′ untranslated region of DEFA5 were associated with IgAN risk.

Metabolic markers, offering sensitive information on biological dysfunction, play important roles in diagnosing and treating cancers. However, the discovery of effective markers is limited by the lack of well-established metabolite selection approaches. Here, we propose a network-based strategy to uncover the metabolic markers with potential clinical availability for non-small cell lung cancer (NSCLC). First, an integrated mass spectrometry-based untargeted metabolomics was used to profile the plasma samples from 43 NSCLC patients and 43 healthy controls. We found that a series of 39 metabolites were altered significantly. Relying on the human metabolic network assembled from Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we mapped these differential metabolites to the network and constructed an NSCLC-related disease module containing 23 putative metabolic markers. By measuring the PageRank centrality of molecules in this module, we computationally evaluated the network-based importance of the 23 metabolites and demonstrated that the metabolism pathways of aromatic amino acids and long-chain fatty acids provided potential molecular targets of NSCLC (i.e., IL4l1 and ACOT2). Combining network-based ranking and support-vector machine modeling, we further found a panel of eight metabolites (i.e., pyruvate, tryptophan, and palmitic acid) that showed a high capability to differentiate patients from controls (accuracy > 97.7%). In summary, we present a meaningful network method for metabolic marker discovery and have identified eight strong candidate metabolites for NSCLC diagnosis.

Astragali radix (AR, the dried root of Astragalus) is a popular herbal remedy in both China and the United States. The commercially available AR is commonly classified into premium graded (PG) and ungraded (UG) ones only according to the appearance. To uncover novel sensitive and specific markers for AR grading, we took the integrated mass spectrometry-based untargeted and targeted metabolomics approaches to characterize chemical features of PG and UG samples in a discovery set (n=16 batches). A series of five differential compounds were screened out by univariate statistical analysis, including arginine, calycosin, ononin, formononetin, and astragaloside Ⅳ, most of which were observed to be accumulated in PG samples except for astragaloside Ⅳ. Then, we performed machine learning on the quantification data of five compounds and constructed a logistic regression prediction model. Finally, the external validation in an independent validation set of AR (n=20 batches) verified that the five compounds, as well as the model, had strong capability to distinguish the two grades of AR, with the prediction accuracy > 90%. Our findings present a panel of meaningful candidate markers that would significantly catalyze the innovation in AR grading., Graphical abstract Image 1, Highlights • Five specific and reliable markers are uncovered to distinguish two grades of AR. • A logistic regression prediction model is built, with an accuracy of > 90%. • Most markers, but not astragaloside Ⅳ, exhibit accumulation in premium graded AR. • The findings are validated in an independent set by targeted LC-MS/MS analysis.

Cisplatin is a chemotherapeutic agent widely employed in the treatment of various solid tumors. However, its use is often restricted by acute kidney injury (AKI) which is the dose-limiting adverse effect of cisplatin. While numerous studies aiming to alleviate the AKI have been conducted, there are no effective remedies in clinical practice. In this paper, a targeted metabolomics study was performed to reveal the potential relationship between tryptophan metabolism and cisplatin-induced AKI. A chemical derivatization integrated liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) approach was utilized to quantify 29 metabolites in the tryptophan pathway in rat kidney medulla and cortex after cisplatin administration. Results showed that tryptophan metabolism was remarkably disturbed both in the medulla and cortex after cisplatin administration. We also found that the tryptophan pathway in the medulla was more sensitive to cisplatin exposure compared with the cortex. Among these metabolites, indoxyl sulfate was focused for further study because it accumulated most significantly in the kidney cortex and medulla in a dose-dependent manner. A function verification study proved that chlormethiazole, a widely used CYP2E1 inhibitor, could reduce the production of indoxyl sulfate in the liver and attenuate cisplatin-induced AKI in rats. In conclusion, our study depicted the tryptophan pathway in cisplatin-induced AKI for the first time and demonstrated tryptophan metabolism is closely associated with the renal toxicity caused by cisplatin, which can be of great use for the discovery of renal toxicity attenuating remedies.

The nervous system disorders caused by doxorubicin (DOX) are among the severe adverse effects that dramatically reduce the quality of life of cancer survivors. Astragali Radix (AR), a popular herbal drug and dietary supplement, is believed to help treat brain diseases by reducing oxidative stress and maintaining metabolic homeostasis. Here we show the protective effects of AR against DOX-induced oxidative damage in rat brain via regulating amino acid homeostasis. By constructing a clinically relevant low-dose DOX-induced toxicity rat model, we first performed an untargeted metabolomics analysis to discover specific metabolic features in the brain after DOX treatment and AR co-treatment. It was found that the amino acid (AA) metabolism pathways altered most significantly. To accurately characterize the brain AA profile, we established a sensitive, fast, and reproducible hydrophilic interaction chromatography–tandem mass spectrometry method for the simultaneous quantification of 22 AAs. The targeted analysis further confirmed the changes of AAs between different groups of rat brain. Specifically, the levels of six AAs, including glutamate, glycine, serine, alanine, citrulline, and ornithine, correlated (Pearson |r| > 0.47, p

Huang-Qin Decoction (HQD) is a classic prescription for diarrhea in Chinese medicine treatment. Recent studies have demonstrated that HQD and its modified formulation PHY906 could ameliorate irinotecan (CPT-11) induced gastrointestinal (GI) toxicity and enhance its anticancer therapeutic efficacy. Nevertheless, which constituents in HQD are effective is still unclear so far. The study aims to screen out the key bioactive components combination from HQD that could enhance the anticancer effect of CPT-11. First, the potential bioactive constituents were obtained through system pharmacology strategy. Then the bioactivity of each constituent was investigated synthetically from the aspects of NCM460 cell migration, TNF-α release of THP-1-derived macrophage and MTT assay in HCT116 cell. The contribution of each constituent in HQD was evaluated using the bioactive index Ei, which taken the content and bioactivity into comprehensive consideration. And then, the most contributing constituents were selected out to form a key-component combination. At last, the bioefficacy of the key-component combination was validated in vitro and in vivo. As a result, a key-component combination (HB4) consisting of four compounds baicalin, baicalein, glycyrrhizic acid and wogonin was screened out. In vitro assessment indicated that HB4 could enhance the effect of CPT-11 on inhibiting cell proliferation and inducing apoptosis in HCT116. Furthermore, the in vivo study confirmed that HB4 and HQD have similar pharmacological activity and could both enhance the antitumor effect of CPT-11 in HCT116 xenograft model. Meanwhile, HB4 could also reduce the CPT-11 induced GI toxicity.

Intestinal toxicity induced by chemotherapeutics has become an important reason for the interruption of therapy and withdrawal of approved agents. In this study, we demonstrated that chemotherapeutics-induced intestinal damage were commonly characterized by the sharp upregulation of tryptophan (Trp)−kynurenine (KYN)−kynurenic acid (KA) axis metabolism. Mechanistically, chemotherapy-induced intestinal damage triggered the formation of an interleukin-6 (IL-6)−indoleamine 2,3-dioxygenase 1 (IDO1)−aryl hydrocarbon receptor (AHR) positive feedback loop, which accelerated kynurenine pathway metabolism in gut. Besides, AHR and G protein-coupled receptor 35 (GPR35) negative feedback regulates intestinal damage and inflammation to maintain intestinal integrity and homeostasis through gradually sensing kynurenic acid level in gut and macrophage, respectively. Moreover, based on virtual screening and biological verification, vardenafil and linagliptin as GPR35 and AHR agonists respectively were discovered from 2388 approved drugs. Importantly, the results that vardenafil and linagliptin significantly alleviated chemotherapy-induced intestinal toxicity in vivo suggests that chemotherapeutics combined with the two could be a promising therapeutic strategy for cancer patients in clinic. This work highlights GPR35 and AHR as the guardian of kynurenine pathway metabolism and core component of defense responses against intestinal damage., Graphical abstract AHR and GPR35 constitute a rationale of defense responses against chemotherapy-induced intestinal damage through gradually sensing Trp–KYN–KA axis metabolism. The formation of IL-6–IDO1–AHR positive feedback loop is driven by AHR through sensing Trp–KYN–KA axis metabolism. AHR and GPR35 sense KA level in a gradient-dependent manner to maintain intestinal integrity and homeostasis.Image 1

Recently, chemoselective probes have gained increasing attention for its superior properties in analyte separation, target compound enrichment, metabolite modification, and derivatization. In this regard, the chemoselective probe is showing great potential in targeted metabolomics research. This review summarizes the workflow and design of chemoselective probes. The new development of its applications in the fields of natural product enrichment, metabolite derivatization, as well as potential applications in metabolomics research is reviewed. Its possible future trends are also prospected.

Acylcarnitines (ACs) play important roles in the fatty acid β-oxidation and are considered as diagnostic markers for many diseases. Accurate determination of ACs remains challenging due to their low abundance, high structure diversity, and limited availability of standard compounds. In this study, microwave-assisted Tmt-PP (p-[3,5-(dimethylamino)-2,4,6-triazine] benzene-1-sulfonyl piperazine) derivatization was utilized to facilitate the liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) determination of ACs. The result indicated that Tmt-PP labeling enables the prediction of the retention time and MS response of ACs and enhances their MS response up to 4 times. The introduction of the microwave during the derivatization procedure greatly improved the reaction efficiency, demonstrated by the shortened reaction time from 90 to 1 min. Furthermore, we applied a strategy named quantitative analysis of multi-components by a single marker (QAMS) for the assay of 26 ACs with only 5 AC standards, solving the standard availability issue to a large extent. The established workflow was applied to discover dysregulated ACs in xenograft colon cancer mice, and the quantification results were highly comparable with traditional methods where there were the corresponding standards for each AC. Our study demonstrated that chemical derivatization-based LC-MS/MS integrated with the QAMS strategy is robust for the identification and quantification of ACs and has great potential in targeted metabolomics study.

FOLFOX (oxaliplatin, fluorouracil and calcium folinate) is the first-line chemotherapy regimen for colon cancer therapy in the clinic. It provides superior efficacy than oxaliplatin alone, but the underlying mechanism remains unclear. In the present study, pharmacomicrobiomics integrated with metabolomics was conducted to uncover the role of the gut microbiome behind this. First, in vivo study demonstrated that FOLFOX exhibited better efficacy than oxaliplatin alone in colon cancer animal models. Second, 16S rDNA gene sequencing analysis showed that the abundance of Akkermansia muciniphila (A. muciniphila) remarkably increased in the FOLFOX treated individuals and positively correlated with the therapeutic effect. Third, further exploration confirmed A. muciniphila colonization significantly enhanced the anti-cancer efficacy of FOLFOX. Last, metabolomics analysis suggested dipeptides containing branched-chain amino acid (BCAA) might be responsible for gut bacteria mediated FOLFOX efficacy. In conclusion, our study revealed the key role of A. muciniphila in mediating FOLFOX efficacy, and manipulating A. muciniphila might serve as a novel strategy for colon cancer therapy.

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with high mortality worldwide. Type 2 diabetes mellitus (T2D), known as a risk factor of CRC, can promote the deterioration of CRC, but the underlying mechanism is elusive. In this study, we aimed to reveal the relationship between CRC and T2D from the perspective of small-molecule metabolism. First, a list of common dysregulated metabolites in CRC and T2D was obtained by retrieving existing metabolomics publications. Among these metabolites, oleic acid (OA) was found to be able to promote the proliferation and migration of colon carcinoma cell HCT116. Further experiments proved that insulin could significantly strengthen this promotion and showed a synergistic effect with OA. Mechanism study found that OA and insulin acted synergistically through the extracellular signal-regulated kinase (ERK)1/2/c-Myc/cyclin D1 pathway. In addition, the combination of ERK1/2 inhibitor SCH772984 and cyclin-dependent kinase (CDK)4/6 inhibitor palbociclib showed a remarkable inhibitory effect on tumor growth in vivo. Taken together, the current study found that OA plays an important role in CRC development by using a functional metabolomics approach. More importantly, insulin and OA were confirmed to synergistically promote the deterioration of CRC in vitro and in vivo via ERK1/2/c-Myc/cyclin D1 pathway. Our findings may shed light on CRC treatment among the T2D population.

Metabolomics, a technique that profiles global small molecules in biological samples, has been a pivotal tool for disease diagnosis and mechanism research. The sample type in metabolomics covers a wide range, including a variety of body fluids, tissues, and cells. However, little attention was paid to the smaller, relatively independent partition systems in cells, namely the organelles. The organelles are specific compartments/places where diverse metabolic activities are happening in an orderly manner. Metabolic disorders of organelles were found to occur in various pathological conditions such as inherited metabolic diseases, diabetes, cancer, and neurodegenerative diseases. However, at the cellular level, the metabolic outcomes of organelles and cytoplasm are superimposed interactively, making it difficult to describe the changes in subcellular compartments. Therefore, characterizing the metabolic pool in the compartmentalized system is of great significance for understanding the role of organelles in physiological functions and diseases. So far, there are very few research articles or reviews related to subcellular metabolomics. In this review, subcellular fractionation and metabolite analysis methods, as well as the application of subcellular metabolomics in the physiological and pathological studies are systematically reviewed, as a practical reference to promote the continued advancement in subcellular metabolomics.

Chronic heart failure (CHF) is an ongoing clinical syndrome with cardiac dysfunction that can be traced to alterations in cardiac metabolism. The identification of metabolic biomarkers in easily accessible fluids to improve the early diagnosis of CHF has been elusive to date. In this study, we took multidimensional analytical techniques to discover potentially new diagnostic biomarkers by focusing on the dynamic changes of metabolites in serum during the progression of CHF. Using mass-spectrometry-based untargeted metabolomics, we identified 23 cardiac metabolites that were altered in a rat model of myocardial infarction induced CHF. Among these differential metabolites, branched-chain amino acids (BCAAs) in serum, especially leucine and valine, showed a high capability to differentiate between CHF and sham-operated rats, of which area under the receiver operating characteristic curve was greater than 0.75. Combining with targeted analysis of the amino acids and related proteins and genes, we confirmed that BCAA metabolic pathway was significantly inhibited in rat failing hearts. On the basis of the time series data of serum samples, we characterized the fluctuation pattern of circulating BCAAs by the disease progression model. Finally, the time-resolved diagnostic potential of serum BCAAs was evaluated by the machine-learning-based classifier, and high diagnostic accuracy of 93.75% was achieved within 3 weeks after surgery. These findings provide a promising metabolic signature that can be further exploited for CHF early diagnostic development.

Pharmacometabolomics has been already successfully used in toxicity prediction for one specific adverse effect. However in clinical practice, two or more different toxicities are always accompanied with each other, which puts forward new challenges for pharmacometabolomics. Gastrointestinal toxicity and myelosuppression are two major adverse effects induced by Irinotecan (CPT-11), and often show large individual differences. In the current study, a pharmacometabolomic study was performed to screen the exclusive biomarkers in predose serums which could predict late-onset diarrhea and myelosuppression of CPT-11 simultaneously. The severity and sensitivity differences in gastrointestinal toxicity and myelosuppression were judged by delayed-onset diarrhea symptoms, histopathology examination, relative cytokines and blood cell counts. Mass spectrometry-based non-targeted and targeted metabolomics were conducted in sequence to dissect metabolite signatures in predose serums. Eventually, two groups of metabolites were screened out as predictors for individual differences in late-onset diarrhea and myelosuppression using binary logistic regression, respectively. This result was compared with existing predictors and validated by another independent external validation set. Our study indicates the prediction of toxicity could be possible upon predose metabolic profile. Pharmacometabolomics can be a potentially useful tool for complicating toxicity prediction. Our findings also provide a new insight into CPT-11 precision medicine., Graphical abstract Mass spectrometry-based non-targeted and targeted metabolomics were conducted in sequence to screen the exclusive biomarkers in predose serums. Based on the pharmacometabolomic analysis, two prediction models were constructed to predict gastrointestinal toxicity and myelosuppression of CPT-11 simultaneously, followed by verification of relevant chemotherapeutic toxicity evaluation indexes.fx1

Intestinal ischemia–reperfusion (IIR) is a life-threatening clinical event with damaging signals whose origin and contents are unclear. Here we observe that IIR significantly affect the metabolic profiles of most organs by unbiased organ-wide metabolic analysis of gut contents, blood, and fifteen organs in rats (n = 29). Remarkably, correlations between gut content metabolic profiles and those of other organs are the most significant. Gut contents are also the only ones to show dynamic correlations during IIR. Additionally, according to targeted metabolomics analysis, several neurotransmitters are considerably altered in the gut during IIR, and displayed noteworthy correlations with remote organs. Likewise, metagenomics analysis (n = 35) confirm the effects of IIR on gut microbiota, and identify key species fundamental to the changes in gut metabolites, particularly neurotransmitters. Our multi-omics results establish key roles of gut contents in IIR induced remote injury and provide clues for future exploration.

Irinotecan (CPT-11) in combination with 5-fluorouracil and leucovorin is a first-line chemotherapy regimen for the treatment of colorectal cancer; however, its clinical application is limited by the dose-limiting gastrointestinal toxicity of colitis. In our previous studies, several bile acids (BAs) were found significantly elevated in the colon of the CPT-11-induced rat colitis model. On the other hand, NLRP3 inflammasome has been reported to play important roles in mediating colitis. Interestingly, BA was stated to activate the NLRP3 inflammasome in some studies, while in some other reports, it showed an inhibitory effect. We assumed that the inflammatory status in different circumstances might have contributed to the controversial findings. In this study, we first discovered, under non-inflammatory conditions, that supplementing BA could activate the NLRP3 inflammasome in THP-1-differentiated macrophages and promote inflammation. In lipopolysaccharide (LPS)-induced inflammatory macrophages, however, BA inhibited the NLRP3 inflammasome and reduced inflammation. Further experiments demonstrated that Takeda G protein-coupled receptor 5 (TGR5) is essential in mediating the inhibitory effect of BA, while phospho-SP1 (p-SP1) is key to the activation. Furthermore, we applied the above findings to ameliorate CPT-11-caused colitis in rats by inhibiting SP1 with mithramycin A (MitA) or activating TGR5 using oleanolic acid (OA). Our findings may shed light on the discovery of effective interventions for reducing dose-limiting chemotherapy-induced colitis.

While FOLFOX has been the preferred chemotherapeutic strategy in colon cancer treatment, the limited response rate has seriously restricted its application in clinic. The underlying mechanisms of the individual response of FOLFOX remain to be elucidated. In this study, pharmacomicrobiomics integrated with pharmacometabolomics was applied to disentangle the key role of specific gut bacteria and microbiota derived metabolites involved. As a result , significant variation of chemotherapy efficacy was observed in tumor bearing mice after FOLFOX administration. 16S rRNA gene sequencing analysis revealed the relative abundance of Staphylococcus , Jeotgalicoccus , Sphingomonas significantly increased in the FOLFOX sensitive group, whereas Prevotella was higher in the non sensitive individuals . Meanwhile, verification study o n FOLFOX combined with bacteria colonization indicates that Prevotella could attenuate the anti cancer efficacy of FOLFOX in vivo . Furthermore, gut derived metabolite 3-Oxocholic acid (3-Oxo) identified by metabolomics approach was confirmed to associate with Prevotella in fecal samples. In addition, preliminary functional exploration suggested that 3-Oxo could reverse the anti cancer effect of FOLFOX and promote malignant progression Taken together, integrated pharmacomicrobiomics and pharmacometabolomics revealed that Prevotella and related metabolite 3-Oxo may be responsible for individualized FOLFOX efficacy, which provides novel predictive biomarkers for FOLFOX precise medicine as well as targets for colon cancer therapy.

This study centers on automatic sleep staging with a single channel electroencephalography (EEG), with some significant findings for sleep staging. In this study, we proposed a deep learning-based network by integrating attention mechanism and bidirectional long short-term memory neural network (AT-BiLSTM) to classify wakefulness, rapid eye movement (REM) sleep and non-REM (NREM) sleep stages N1, N2 and N3. The AT-BiLSTM network outperformed five other networks and achieved an accuracy of 83.78%, a Cohen’s kappa coefficient of 0.766 and a macro F1-score of 82.14% on the PhysioNet Sleep-EDF Expanded dataset, and an accuracy of 81.72%, a Cohen’s kappa coefficient of 0.751 and a macro F1-score of 80.74% on the DREAMS Subjects dataset. The proposed AT-BiLSTM network even achieved a higher accuracy than the existing methods based on traditional feature extraction. Moreover, better performance was obtained by the AT-BiLSTM network with the frontal EEG derivations than with EEG channels located at the central, occipital or parietal lobe. As EEG signal can be easily acquired using dry electrodes on the forehead, our findings might provide a promising solution for automatic sleep scoring without feature extraction and may prove very useful for the screening of sleep disorders.

Astragali Radix (AR) is a popular traditional Chinese medicine that has been used for more than 2000 years. It is a well-known tonic for weak people with chronic diseases, such as heart failure and cerebral ischemia. Previous studies have reported that AR could support the "weak heart" of cancer patients who suffered from doxorubicin (DOX)-induced cardiotoxicity (DIC). However, the underlying mechanism remains unclear.This study aimed to uncover the critical pathways and molecular determinants for AR against DIC by fully characterizing the network-based relationship.We integrated ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) profiling, database and literature searching, and the human protein-protein interactome to discover the specific network module associated with AR against DIC. To validate the network-based findings, a low-dose, long-term DIC mouse model and rat cardiomyoblast H9c2 cells were employed. The levels of potential key metabolites and proteins in hearts and cells were quantified by the LC-MS/MS targeted analysis and western blotting, respectively.We constructed one of the most comprehensive AR component-target network described to date, which included 730 interactions connecting 64 unique components and 359 unique targets. Relying on the network-based evaluation, we identified fatty acid metabolism as a putative critical pathway and peroxisome proliferator-activated receptors (PPARα and PPARγ) as potential molecular determinants. We then confirmed that DOX caused the accumulation of fatty acids in the mouse failing heart, while AR promoted fatty acid metabolism and preserved heart function. By inhibiting PPARγ in H9c2 cells, we further found that AR could alleviate DIC by activating PPARγ to maintain fatty acid homeostasis.Our findings imply that AR is a promising drug candidate that treats DIC by maintaining fatty acid homeostasis. More importantly, the network-based method developed here could facilitate the mechanism discovery of AR therapy and help catalyze innovation in its clinical application.

Modified metabolites play significant roles in disease occurrence, progression and diagnosis. Sensitive and accurate analytical methods for the quantification of these metabolites are therefore of great importance. In this study, a liquid chromatography tandem mass spectrometry (LC-MS/MS) method was developed for the simultaneous measurement of 13 pairs of prototypes and their modified forms covering nucleobases, nucleosides and amino acids. In order to improve the quantification sensitivity and accuracy, two structure analogs named N-dimethyl-amino naphthalene-1-sulfonyl chloride (Dns-Cl) and N-diethyl-amino naphthalene-1-sulfonyl chloride (Dens-Cl) were introduced for twins labeling derivatization. Dns-labeling was utilized to react with target analytes while the Dens-labeling of standard compounds provided one-to-one internal standards. With the introduce of naphthalene and easily ionizable moiety tertiary ammonium, chromatography retention and separation of these polar metabolites were notably improved on C18 columns and the detection sensitivity was increased up to 400 folds. The method is sensitive with the lower limit of quantification (LLOQ) values of 0.002-0.5 μg/mL. Comparisons of the performance of twins labeling derivatization and traditional chemical isotope labeling (CIL) derivatization verified the ability of our method in the absolute quantification. The established method was applied to human lung adenocarcinoma cell line A549 and its cisplatin resistant derivative A549/DDP. Significant shifts in 12 metabolites as well as 9 modified-to-prototypical ratios in A549/DDP were observed, demonstrating the utility of our method and the potential role of modified metabolites in mediating anticancer drug resistance. The method can be easily extended to determine other types of modified metabolites in various biological matrices, which will greatly expand our knowledge on these metabolites.

Background Intestinal obstruction (IO) is a kind of acute abdomen with high morbidity and mortality. Patients suffer from poor quality of life and tremendous financial pressure. Da-Cheng-Qi decoction (DCQD), a classical purgation prescription, has clinically been proven to be an effective treatment for IO. Purpose Network pharmacology integrated with bioactive equivalence assessment was used to discover the quality marker (Q-marker) of DCQD against IO. Methods As there is hardly any targets recorded in database, thus the collection of IO targets was conducted by searching those of alternative diseases which have similar pathological symptoms with IO. In order to improve the reliability of the obtained targets, IO metabolomics data was introduced. Active compounds combination (ACC) was focused as potential Q-markers via component-target network analysis and function query from the identified components corresponding to the common targets. Bioequivalence between ACC and DCQD was assessed from the aspects of intestine motility (somatostatin secretion), inflammation (IL-6 secretion) and injury (wound healing assay) in vitro and was further validated in ileus rat model. PPI network analysis of core targets followed by gene pedigree classification and experimental validation confirmed the potential intervention pathway. Results A combination of 11 ingredients, including emodin, physcion, aloe-emodin, rhein, chrysophanol, gallic acid, magnolol, honokiol, naringenin, tangeretin, and nobiletin was finally confirmed bioequivalence with DQCD to some extent and could serve as Q-markers for DCQD to attenuate IO. PI3K/AKT was verified as a possible affected pathway that DCQD exerted the effectiveness against IO. Conclusion For the disease with few recorded targets, searching those of alternative diseases which have similar pathological symptoms could be a feasible and effective approach. The proposed network pharmacology integrated bioactive equivalence evaluation paradigm is efficient to discover Q-marker of herbal formulae.

Intestinal ischemia-reperfusion injury (IIR) is a life-threatening abdominal emergency. Compared to traditional steady-state works, we profiled the blood of rats over 72 hr (15 time points) and examined dynamic changes in molecular pathways during IIR. Using a series of methods designed for dynamic datasets analysis (batch effects corrections, metabolomics data reduction, and different features selection), we identified 39 significant different metabolites and discovered the trends of these molecules. Four main patterns were uncovered by a longitudinal pattern recognition method. Furthermore, pathway networks were explored to uncover the possible mechanisms of IIR. We found that IIR is a complex physiological process involved in multiple pathways, such as biosynthesis of amino acids, 2-oxocarboxylic acid metabolism, arginine-related metabolism, and glutathione metabolism. Among which, metabolites related with phenylalanine tyrosine and tryptophan metabolism reached a peak during the early stage of reperfusion, while molecules in biosynthesis of unsaturated fatty acids metabolism declined. Our work provides a feasible scheme to understand dynamic molecule variation and will provide new explications about the effect of intestinal ischemia reperfusion from a dynamic perspective.

To better understand different traditional uses of the stems (known as Mahuang) and roots (known as Mahuanggen) of Ephedra sinica, their chemical difference should be investigated. In this study, an ultra-fast liquid chromatography coupled with ion trap time-of-flight mass spectrometry untargeted metabolomics approach was established to reveal global chemical difference between Mahuang and Mahuanggen. Clear separation was observed in scores plots of principal component analysis and orthogonal partial least squares-discriminant analysis. Twenty two chemical markers responsible for such separation were screened out and unambiguously/tentatively characterized. Then chemical markers of pharmacologically important ephedrine and pseudoephedrine were absolutely quantified using liquid chromatography coupled with tandem mass spectrometry under multiple reaction monitoring mode. The results showed that Mahuang was rich in ephedrine-type alkaloids, while Mahuanggen was rich in macrocyclic spermine alkaloids. Additionally, different types of flavan-3-ols and flavones exist in Mahuang and Mahuanggen extracts. This research facilitates a better understanding of different traditional uses of Mahuang and Mahuanggen and provides references for chemical analysis of other medicinal plants.

Nephrotoxicity is the dose-limiting adverse effect of cisplatin with large individual differences. Up to now, little has been done on how to recognize and predict the individual differences in either preclinical or clinical research. In the present study, important postdose indicators were screened out first and integrated into a grouping factor, according to which rats were recognized as lowly or highly sensitive individuals. Then, mass-spectrometry-based untargeted metabolomics approach was performed to dissect the metabolic differences in predose serum of the two groups. Eventually, branched-chain amino acids (BCAAs) were found to be most significant with the lowest p value of Mann-Whitney U test and the highest area under receiving operating characteristic curve (AUC-ROC). The findings were further confirmed by absolute quantitation of BCAAs using liquid chromatography-tandem mass spectrometry. Binary logistic regression showed that in the discovery set absolute BCAA contents in rat predose serum could predict cisplatin nephrotoxicity with accuracy of 85%. This result was validated by another two independent external validation sets with accuracy of 81.8 and 78.8%, respectively. This study could provide new insight into cisplatin nephrotoxicity and may help expedite personalized medicine of cisplatin or other antitumor drugs in future clinical studies.

Stroke remains a major public health problem worldwide; it causes severe disability and is associated with high mortality rates. However, early diagnosis of stroke is difficult, and no reliable biomarkers are currently established. In this study, mass-spectrometry-based metabolomics was utilized to characterize the metabolic features of the serum of patients with acute ischemic stroke (AIS) to identify novel sensitive biomarkers for diagnosis and progression. First, global metabolic profiling was performed on a training set of 80 human serum samples (40 cases and 40 controls). The metabolic profiling identified significant alterations in a series of 26 metabolites with related metabolic pathways involving amino acid, fatty acid, phospholipid, and choline metabolism. Subsequently, multiple algorithms were run on a test set consisting of 49 serum samples (26 cases and 23 controls) to develop different classifiers for verifying and evaluating potential biomarkers. Finally, a panel of five differential metabolites, including serine, isoleucine, betaine, PC(5:0/5:0), and LysoPE(18:2), exhibited potential to differentiate AIS samples from healthy control samples, with area under the receiver operating characteristic curve values of 0.988 and 0.971 in the training and test sets, respectively. These findings provided insights for the development of new diagnostic tests and therapeutic approaches for AIS.

Background: Obstructive sleep apnea (OSA), a highly prevalent sleep disorder, is closely related to cardiovascular disease (CVD). Our previous work demonstrated that Shannon entropy of the degree distribution (EDD), obtained from the network domain of heart rate variability (HRV), might be a potential indicator for CVD. Method: To investigate the potential association between OSA and EDD, OSA patients and healthy controls (HCs) were identified from a sleep study database. Then EDD was calculated from electrocardiogram (ECG) signals during sleep, followed by cross-sectional comparisons between OSA patients and HCs, and longitudinal comparisons from baseline to follow-up visits. Furthermore, for OSA patients, the association between EDD and OSA severity, measured by apnea-hypopnea index (AHI), was also analyzed. Results: Compared with HCs, OSA patients had significantly increased EDD during sleep. A positive correlation between EDD and the severity of OSA was also observed. Although the value of EDD became larger with aging, it was not OSA-specified. Conclusion: Increased EDD derived from ECG signals during sleep might be a potential dynamic biomarker to identify OSA patients from HCs, which may be used in screening OSA with high risk before polysomnography is considered.

Neuroinflammation is one of the driving forces of progressive neurodegeneration in Parkinson's disease (PD). The metabolomics approach has been proved highly useful in identifying potential therapeutic targets. Here, to identify inflammation-relevant treatment targets for PD, mass spectrometry-based untargeted metabolomics was applied to characterize metabolic changes in the striatum of mice with double-hit PD induced by lipopolysaccharide plus 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Seven days after the final MPTP administration, metabolites from the purine metabolism pathway, including adenosine, 1-methyladenosine, adenine, inosine, hypoxanthine, xanthine, xanthosine, and guanosine, were found to be significantly dysregulated. The metabolite-protein interaction network and changes in the concentration ratio of these metabolites indicated that adenosine and adenosine deaminase (ADA; EC 3.5.4.4) were the most promising therapeutic targets and adenosine augmentation might be a rational approach to slow PD progression. These findings were then verified in a subacute MPTP-induced PD mouse model treated with ADA inhibition alone or in conjunction with antagonism of adenosine A2A receptors (A2A R). Behavioral, biochemical, and immunohistochemical analysis demonstrated that ADA inhibition significantly ameliorated the MPTP-mediated motor disabilities, dopamine depletion, and dopaminergic cell death. Significantly enhanced neuroprotective effects were further observed when the ADA inhibitor was utilized in conjunction with an A2A R antagonist. Together, our study indicated for the first time that ADA inhibitors protected against neurodegeneration induced by the neurotoxin MPTP, and ADA inhibitors in combination with A2A R antagonists showed additive antiparkinsonian effects.

Two popular debilitating illness, unipolar depression (UD) and bipolar disorder (BD), have the similar symptoms and tight association on the psychopathological level, leading to a clinical challenge to distinguish them. In order to figure out the underlying common and different mechanism of both mood disorders, resting-state functional magnetic resonance imaging (rs-fMRI) data derived from 36 UD patients, 42 BD patients (specially type I, BD-I) and 45 healthy controls (HC) were analyzed retrospectively in this study. Functional brain networks were firstly constructed on both group and individual levels with a density 0.2, which was determined by a network thresholding approach based on modular similarity. Then we investigated the alterations of modular structure and other topological properties of the functional brain network, including global network characteristics and nodal network measures. The results demonstrated that the functional brain networks of UD and BD-I groups preserved the modularity and small-worldness property. However, compared with HC, reduced number of modules was observed in both patients' groups with shared alterations occurring in hippocampus, para hippocampal gyrus, amygdala and superior parietal gyrus and distinct changes of modular composition mainly in the caudate regions of basal ganglia. Additionally, for the network characteristics, compared to HC, significantly decreased global efficiency and small-worldness were observed in BD-I. For the nodal metrics, significant decrease of local efficiency was found in several regions in both UD and BD-I, while a UD-specified increase of participant coefficient was found in the right paracentral lobule and the right thalamus. These findings may contribute to throw light on the neuropathological mechanisms underlying the two disorders and further help to explore objective biomarkers for the correct diagnosis of UD and BD.

Cisplatin is a potent chemotherapeutic agent. However, its clinical usage is restricted by serious adverse effects, especially nephrotoxicity. For revealing the dose- and time-dependence of cisplatin-induced nephrotoxicity, mass spectrometry-based metabolomics integrated with a principal component-based area calculation (PCAC) strategy was proposed in the present study. Area plots based on the first two principal components of the principal component analysis model were constructed first. Then, the sums of cumulative areas under PC-T curves (AUCPC-T) were calculated. Finally, the fold change of AUCPC-T between experimental and control groups at different time points was calculated and used as an indicative parameter. With the PCAC approach, dose- and time-dependence of cisplatin-induced metabolic change was quantitatively confirmed for the first time. Furthermore, 27 potential biomarkers with dose- and time-dependence related to nephrotoxicity induced by cisplatin were screened out and tentatively identified. Metabolic pathways interrupted by cisplatin mainly included energy, amino acid, and lipid metabolism.

Time-series metabolomics studies can provide snapshots of the metabolic status during the progress of disease and drug treatment. In order to reveal the dynamic development of a disease, a pseudo-kinetics approach based on calibration and integration of absolute fold changes (FCk) along the time points was proposed. A distance based discriminative trajectory was applied to assess global metabolic alterations during ileus progress upon principle component analysis (PCA). The area under the curve (AUC) and peak time (Tmax) of the absolute FCk–time curve were integrated as complementary thresholds to screen sensitive biomarkers compared with the typical ileus parameters of gastric emptying (GE) and gastrointestinal transit (GI). As a result, docosahexaenoic acid, glycocholic acid, glutamine and acetyl-carnitine were identified as sensitive biomarkers for early prediction of paralytic ileus, which were related to intestinal inflammation and mucosal injury. Furthermore, the discrimination abilities of these four biomarkers were validated using receiver-operating characteristic (ROC) analysis. Collectively, this study demonstrated that our proposed pseudo-kinetics approach is effective to screen more reliable and sensitive biomarkers along a pathologic progress.