A Clinical Breathomics Dataset.

This study entailed a comprehensive GC‒MS analysis conducted on 121 patient samples to generate a clinical breathomics dataset. Breath molecules, indicative of diverse conditions such as psychological and pathological states and the microbiome, were of particular interest due to their non-invasive nature. The highlighted noninvasive approach for detecting these breath molecules significantly enhances diagnostic and monitoring capacities. This dataset cataloged volatile organic compounds (VOCs) from the breath of individuals with asthma, bronchiectasis, and chronic obstructive pulmonary disease. Uniform and consistent sample collection protocols were strictly adhered to during the accumulation of this extensive dataset, ensuring its reliability. It encapsulates extensive human clinical breath molecule data pertinent to three specific diseases. This consequential clinical breathomics dataset is a crucial resource for researchers and clinicians in identifying and exploring important compounds within the patient's breath, thereby augmenting future diagnostic and therapeutic initiatives.

MetaMOPE: a web service for mobile phase determination and fast chromatography peaks evaluation for metabolomics.

Motivation: Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used in metabolomics studies, while HILIC LC-MS is particularly suited for polar metabolites. Determining an optimized mobile phase and developing a proper liquid chromatography method tend to be laborious, time-consuming and empirical. Results: We developed a containerized web tool providing a workflow to quickly determine the optimized mobile phase by batch-evaluating chromatography peaks for metabolomics LC-MS studies. A mass chromatographic quality value, an asymmetric factor, and the local maximum intensity of the extracted ion chromatogram were calculated to determine the number of peaks and peak retention time. The optimal mobile phase can be quickly determined by selecting the mobile phase that produces the largest number of resolved peaks. Moreover, the workflow enables one to automatically process the repeats by evaluating chromatography peaks and determining the retention time of large standards. This workflow was validated with 20 chemical standards and successfully constructed a reference library of 571 metabolites for the HILIC LC-MS platform. Availability and implementation: MetaMOPE is freely available at https://metamope.cmdm.tw. Source code and installation instructions are available on GitHub: https://github.com/CMDM-Lab/MetaMOPE. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

MSIr: Automatic Registration Service for Mass Spectrometry Imaging and Histology.

Mass spectrometry imaging (MSI) is a powerful tool that can be used to simultaneously investigate the spatial distribution of different molecules in samples. However, it is difficult to comprehensively analyze complex biological systems with only a single analytical technique due to different analytical properties and application limitations. Therefore, many analytical methods have been combined to extend data interpretation, evaluate data credibility, and facilitate data mining to explore important temporal and spatial relationships in biological systems. Image registration is an initial and critical step for multimodal imaging data fusion. However, the image registration of multimodal images is not a simple task. The property difference between each data modality may include spatial resolution, image characteristics, or both. The image registrations between MSI and different imaging techniques are often achieved indirectly through histology. Many methods exist for image registration between MSI data and histological images. However, most of them are manual or semiautomatic and have their prerequisites. Here, we built MSI Registrar (MSIr), a web service for automatic registration between MSI and histology. It can help to reduce subjectivity and processing time efficiently. MSIr provides an interface for manually selecting region of interests from histological images; the user selects regions of interest to extract the corresponding spectrum indices in MSI data. In the performance evaluation, MSIr can quickly map MSI data to histological images and help pinpoint molecular components at specific locations in tissues. Most registrations were adequate and were without excessive shifts. MSIr is freely available at https://msir.cmdm.tw and https://github.com/CMDM-Lab/MSIr.

Taiwan Controlled Substances Database.

New psychoactive substances (NPS) have increasingly been illegally synthesized and used around the world in recent years. Due to the large volume and the variety of NPS, most do not have sufficient information about their addictive potential and harmful effects to human subjects. This makes it difficult to evaluate these potential substances of abuse. This study aims to build a database based on Taiwan's controlled substances, to provide quick structural and pharmacological feedback. Taiwan Controlled Substances Database (TCSD) includes the collection of controlled substances, relevant experimental and structural information, as well as computational features such as molecular fingerprints and descriptors. Two types of structural search were added: substructure search and topological fingerprint similarity search. A web framework was used to enhance accessibility and usability (https://cs2search.cmdm.tw).

RSDB: A rare skin disease database to link drugs with potential drug targets for rare skin diseases.

Rare skin diseases include more than 800 diseases affecting more than 6.8 million patients worldwide. However, only 100 drugs have been developed for treating rare skin diseases in the past 38 years. To investigate potential treatments through drug repurposing for rare skin diseases, it is necessary to have a well-organized database to link all known disease causes, mechanisms, and related information to accelerate the process. Drug repurposing provides less expensive and faster potential options to develop treatments for known diseases. In this work, we designed and constructed a rare skin disease database (RSDB) as a disease-centered information depository to facilitate repurposing drug candidates for rare skin diseases. We collected and integrated associated genes, chemicals, and phenotypes into a network connected by pairwise relationships between different components for rare skin diseases. The RSDB covers 891 rare skin diseases defined by the Orphanet and GARD databases. The organized network for each rare skin disease comprises associated genes, phenotypes, and chemicals with the corresponding connections. The RSDB is available at https://rsdb.cmdm.tw .

Coexisting gastrointestinal and hepatobiliary tract anomalies in omphalocele and gastroschisis: A twenty-year experience in a single tertiary medical center.

BACKGROUND: Omphalocele and gastroschisis are the two most common congenital abdominal wall defects; however, no previous study has focused on gastrointestinal and hepatobiliary tract malformations in these two conditions. This study aimed to investigate the demographic characteristics, coexisting congenital gastrointestinal and hepatobiliary tract anomalies, hospital course, and outcomes of patients with gastroschisis and omphalocele. METHODS: This is retrospective chart review of all patients admitted to one tertiary medical center in Taiwan between January 1, 2000 and June 30, 2020 with a diagnosis of gastroschisis or omphalocele. The medical records were reviewed to obtain demographic data regarding coexisting gastrointestinal and hepatobiliary tract anomalies and outcomes. RESULTS: Of the 51 patients included, 21 had gastroschisis and 30 had omphalocele. Gastroschisis was associated with a significantly younger maternal age and a higher incidence of small for gestational age. Of the 30 patients with omphalocele, twelve had associated gastrointestinal and hepatobiliary anomalies. Seven of the 21 patients with gastroschisis had gastrointestinal anomalies, and none had hepatobiliary anomalies. Among the omphalocele patients, three (10%) had documented malrotation, and one developed midgut volvulus. Among gastroschisis patients, four patients (19%) had malrotation, and two developed midgut volvulus. There were no statistically significant differences in postoperative complications or mortality rates between those with and without gastrointestinal/hepatobiliary tract anomalies. CONCLUSION: The diversity of coexisting gastrointestinal and hepatobiliary tract anomalies is higher in the omphalocele than in gastroschisis. In addition, we demonstrate that patients with gastroschisis or omphalocele have a higher rate of intestinal malrotation and midgut volvulus.

A pilot study of metabolomic pathways associated with fatigue in patients with colorectal cancer receiving chemotherapy.

PURPOSE: The aim of this pilot study was to evaluate for differences in metabolomic profiles between fatigued and non-fatigued patients with colorectal cancer (CRC) during chemotherapy (CTX). METHOD: Patients were recruited from the department of surgery in a large medical center in Taiwan. In this longitudinal pilot study, the Fatigue Symptom Inventory and fasting blood samples were collected at three assessments (i.e., prior to surgery (T0), three months (T1) and six months (T2) after surgery). Metabolomic profile analysis was used. Multilevel regression and pathway analyses were performed to identify differences in metabolomic profiles between the fatigued and non-fatigued groups. RESULTS: Of the 49 patients, 55.1% (n = 27) were in the fatigue group. All of the 15 metabolites that had statistically significant group × time interactions in the differential metabolite analysis were entered into the pathway analysis. Two pathways were enriched for these metabolites, namely galactose metabolism and phenylalanine, tyrosine, and tryptophan biosynthesis. CONCLUSIONS: The results from this pilot study suggest that pathways involved in galactose metabolism and phenylalanine, tyrosine, and tryptophan biosynthesis are associated with cancer-related fatigue (CRF) in patients with CRC during CTX. These findings are consistent with the hypotheses that alterations in energy metabolism and increases in inflammation are associated with the development and maintenance of CRF.

Lipidomics of children and adolescents exposed to multiple industrial pollutants.

BACKGROUND: There are limited studies on the lipidomics of children and adolescents exposed to multiple industrial pollutants. OBJECTIVES: In this study, we aimed to investigate lipid profile perturbations in 99 children and adolescents (aged 9-15) who lived in a polluted area surrounding the largest petrochemical complex in Taiwan. Previous studies have reported increased risks of acute and chronic diseases including liver dysfunctions and chronic kidney disease (CKD) in residents living in this area. METHODS: We measured urinary concentrations of 11 metals and metalloids and polycyclic aromatic hydrocarbons (PAHs) metabolite 1-hydroxypyrene (1-OHP) as exposure biomarkers, and urinary oxidative stress biomarkers and serum acylcarnitines as early health effect biomarkers. The association between individual exposure biomarkers and early health effect biomarkers were analyzed using linear regression, while association of combined exposure biomarkers with four oxidative stress biomarkers and acylcarnitines were analyzed using weighted quantile sum (WQS) regression. Lipid profiles were analyzed using an untargeted liquid chromatography mass spectrometry-based technique. "Meet-in-the-middle" approach was applied to identify potential lipid features that linked multiple industrial pollutants exposure with early health effects. RESULTS: We identified 15 potential lipid features that linked elevated multiple industrial pollutants exposure with three increased oxidative stress biomarkers and eight deregulated serum acylcarnitines, including one lysophosphatidylcholines (LPCs), four phosphatidylcholines (PCs), and two sphingomyelins (SMs) that were up-regulated in high exposure group compared to low exposure group, and two LPCs, four PCs, and two phosphatidylinositols (PIs) down-regulated in high exposure group compared to low exposure group. CONCLUSION: Our findings could provide information for understanding the health effects, including early indicators and biological mechanism identification, of children and adolescents exposed to multiple industrial pollutants during critical stages of development.

A Pilot Study of Metabolomic Pathways Associated With Fatigue in Survivors of Colorectal Cancer.

BACKGROUND: Over 30% of cancer survivors experience chronic fatigue. An alteration in energy metabolism is one of the hypothesized mechanisms for cancer-related fatigue (CRF). No studies have evaluated for changes in metabolic profiles in cancer survivors with CRF. The purpose of this pilot study was to evaluate for differences in metabolic profiles between fatigued and non-fatigued survivors of colorectal cancer (CRC). METHODS: Survivors were recruited from the surgical outpatient department and the oncology clinic of a medical center in northern Taiwan. Fatigue was assessed using the Fatigue Symptom Inventory. Fasting blood samples were collected on the day the fatigue questionnaire was completed. Metabolomic profile analysis was performed using non-targeted, liquid chromatography/time-of-flight mass spectrometry. Fold change analyses, t-tests, and pathway analyses were performed to identify differences in metabolomic profiles between the fatigued and non-fatigued survivors. RESULTS: Of the 56 CRC survivors in this study, 28.6% (n = 16) were in the fatigue group. Statistically significant differences in carnitine, L-norleucine, pyroglutamic acid, pyrrolidonecarboxylic acid, spermine, hydroxyoctanoic acid, and paraxanthine were found between the two fatigue groups. In addition, two pathways were enriched for these metabolites (i.e., glutathione metabolism, D-glutamine and D-glutamate metabolism). CONCLUSIONS: Findings from this pilot study provide preliminary evidence that two pathways that are involved with the regulation of ATP production and cellular energy (i.e., glutathione metabolism, D-glutamine and D-glutamate metabolism) are associated with fatigue in CRC survivors. If these findings are confirmed, they may provide new therapeutic targets to decrease fatigue in cancer survivors.

Human Breathomics Database.

Breathomics is a special branch of metabolomics that quantifies volatile organic compounds (VOCs) from collected exhaled breath samples. Understanding how breath molecules are related to diseases, mechanisms and pathways identified from experimental analytical measurements is challenging due to the lack of an organized resource describing breath molecules, related references and biomedical information embedded in the literature. To provide breath VOCs, related references and biomedical information, we aim to organize a database composed of manually curated information and automatically extracted biomedical information. First, VOCs-related disease information was manually organized from 207 literature linked to 99 VOCs and known Medical Subject Headings (MeSH) terms. Then an automated text mining algorithm was used to extract biomedical information from this literature. In the end, the manually curated information and auto-extracted biomedical information was combined to form a breath molecule database-the Human Breathomics Database (HBDB). We first manually curated and organized disease information including MeSH term from 207 literatures associated with 99 VOCs. Then, an automatic pipeline of text mining approach was used to collect 2766 literatures and extract biomedical information from breath researches. We combined curated information with automatically extracted biomedical information to assemble a breath molecule database, the HBDB. The HBDB is a database that includes references, VOCs and diseases associated with human breathomics. Most of these VOCs were detected in human breath samples or exhaled breath condensate samples. So far, the database contains a total of 913 VOCs in relation to human exhaled breath researches reported in 2766 publications. The HBDB is the most comprehensive HBDB of VOCs in human exhaled breath to date. It is a useful and organized resource for researchers and clinicians to identify and further investigate potential biomarkers from the breath of patients. Database URL: https://hbdb.cmdm.tw.

Metabolomics of Children and Adolescents Exposed to Industrial Carcinogenic Pollutants.

Studies on metabolomes of carcinogenic pollutants among children and adolescents are limited. We aim to identify metabolic perturbations in 107 children and adolescents (aged 9-15) exposed to multiple carcinogens in a polluted area surrounding the largest petrochemical complex in Taiwan. We measured urinary concentrations of eight carcinogen exposure biomarkers (heavy metals and polycyclic aromatic hydrocarbons (PAHs) represented by 1-hydroxypyrene), and urinary oxidative stress biomarkers and serum acylcarnitines as biomarkers of early health effects. Serum metabolomics was analyzed using a liquid chromatography mass spectrometry-based method. Pathway analysis and "meet-in-the-middle" approach were applied to identify potential metabolites and biological mechanisms linking carcinogens exposure with early health effects. We found 10 potential metabolites possibly linking increased exposure to IARC group 1 carcinogens (As, Cd, Cr, Ni) and group 2 carcinogens (V, Hg, PAHs) with elevated oxidative stress and deregulated serum acylcarnitines, including inosine monophosphate and adenosine monophosphate (purine metabolism), malic acid and oxoglutaric acid (citrate cycle), carnitine (fatty acid metabolism), and pyroglutamic acid (glutathione metabolism). Purine metabolism was identified as the possible mechanism affected by children and adolescents' exposure to carcinogens. These findings contribute to understanding the health effects of childhood and adolescence exposure to multiple industrial carcinogens during critical periods of development.

LipidPedia: a comprehensive lipid knowledgebase.

Motivation: Lipids are divided into fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, saccharolipids, sterols, prenol lipids and polyketides. Fatty acyls and glycerolipids are commonly used as energy storage, whereas glycerophospholipids, sphingolipids, sterols and saccharolipids are common used as components of cell membranes. Lipids in fatty acyls, glycerophospholipids, sphingolipids and sterols classes play important roles in signaling. Although more than 36 million lipids can be identified or computationally generated, no single lipid database provides comprehensive information on lipids. Furthermore, the complex systematic or common names of lipids make the discovery of related information challenging. Results: Here, we present LipidPedia, a comprehensive lipid knowledgebase. The content of this database is derived from integrating annotation data with full-text mining of 3923 lipids and more than 400 000 annotations of associated diseases, pathways, functions and locations that are essential for interpreting lipid functions and mechanisms from over 1 400 000 scientific publications. Each lipid in LipidPedia also has its own entry containing a text summary curated from the most frequently cited diseases, pathways, genes, locations, functions, lipids and experimental models in the biomedical literature. LipidPedia aims to provide an overall synopsis of lipids to summarize lipid annotations and provide a detailed listing of references for understanding complex lipid functions and mechanisms. Availability and implementation: LipidPedia is available at http://lipidpedia.cmdm.tw. Supplementary information: Supplementary data are available at Bioinformatics online.

Web Server for Peak Detection, Baseline Correction, and Alignment in Two-Dimensional Gas Chromatography Mass Spectrometry-Based Metabolomics Data.

Two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) is superior for chromatographic separation and provides great sensitivity for complex biological fluid analysis in metabolomics. However, GC×GC/TOF-MS data processing is currently limited to vendor software and typically requires several preprocessing steps. In this work, we implement a web-based platform, which we call GC2MS, to facilitate the application of recent advances in GC×GC/TOF-MS, especially for metabolomics studies. The core processing workflow of GC2MS consists of blob/peak detection, baseline correction, and blob alignment. GC2MS treats GC×GC/TOF-MS data as pictures and clusters the pixels as blobs according to the brightness of each pixel to generate a blob table. GC2MS then aligns the blobs of two GC×GC/TOF-MS data sets according to their distance and similarity. The blob distance and similarity are the Euclidean distance of the first and second retention times of two blobs and the Pearson's correlation coefficient of the two mass spectra, respectively. GC2MS also directly corrects the raw data baseline. The analytical performance of GC2MS was evaluated using GC×GC/TOF-MS data sets of Angelica sinensis compounds acquired under different experimental conditions and of human plasma samples. The results show that GC2MS is an easy-to-use tool for detecting peaks and correcting baselines, and GC2MS is able to align GC×GC/TOF-MS data sets acquired under different experimental conditions. GC2MS is freely accessible at http://gc2ms.web.cmdm.tw .

Mass-Spectrometry-Based Serum Metabolomics of a C57BL/6J Mouse Model of High-Fat-Diet-Induced Non-alcoholic Fatty Liver Disease Development.

Obesity, dyslipidemia, insulin resistance, oxidative stress, and inflammation are key clinical risk factors for the progression of non-alcoholic fatty liver disease (NAFLD). Currently, there is no comprehensive metabolic profile of a well-established animal model that effectively mimics the etiology and pathogenesis of NAFLD in humans. Here, we report the pathophysiological and metabolomic changes associated with NAFLD development in a C57BL/6J mouse model in which NAFLD was induced by feeding a high-fat diet (HFD) for 4, 8, 12, and 16 weeks. Serum metabolomic analysis was conducted using ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) and gas chromatography-mass spectrometry (GC-MS) to establish a metabolomic profile. Analysis of the metabolomic profile in combination with principal component analysis revealed marked differences in metabolites between the control and HFD group depending upon NAFLD severity. A total of 30 potential biomarkers were strongly associated with the development of NAFLD. Among these, 11 metabolites were mainly related to carbohydrate metabolism, hepatic biotransformation, collagen synthesis, and gut microbial metabolism, which are characteristics of obesity, as well as significantly increased serum glucose, total cholesterol, and hepatic triglyceride levels during the onset of NAFLD (4 weeks). At 8 weeks, 5 additional metabolites that are chiefly involved in perturbation of lipid metabolism and insulin secretion were found to be associated with hyperinsulinemia, hyperlipidemia, and hepatic steatosis in the mid-term of NAFLD progression. At the end of 12 and 16 weeks, 14 additional metabolites were predominantly correlated to abnormal bile acid synthesis, oxidative stress, and inflammation, representing hepatic inflammatory infiltration during NAFLD development. These results provide potential biomarkers for early risk assessment of NAFLD and further insights into NAFLD development.

Fasting but not changes of plasma metabolome during oral glucose tolerance tests improves the diagnosis of severe coronary arterial stenosis.

BACKGROUND: Noninvasive stress tests for the diagnosis of significant coronary arterial stenosis requiring intervention are not perfect. We investigated whether plasma metabolome during the oral glucose tolerance test (OGTT) can improve the diagnosis. METHODS: A total of 117 subjects with positive stress test results who received coronary angiography were recruited. After excluding subjects with a history of myocardial infarction and subjects who did not receive OGTT, the 18 subjects without significant stenosis were selected as controls. Another 18 age- and sex-matched subjects with significant stenosis were selected as cases. Plasma metabolome from samples obtained in fasting, 30 and 120 min after OGTT was measured using liquid chromatography combined with time-of-flight mass spectrometry. RESULTS: We found five metabolites which can identify patients with significant stenosis independent to clinical risk factors, including diabetes, hypertension, hypercholesterolaemia, smoking and history of percutaneous coronary intervention (all P < 0·05). The area under the receiver operating characteristic (AUROC) curve of these metabolites was 0·799-0·818 at fasting and 30 min after OGTT. The addition of metabolites to clinical factors increases the AUROC (0·616, 95%CI 0·429-0·803 for model with clinical factors only; 0·824, 95%CI 0·689-0·959 for model with four metabolites and clinical factors). The changes of plasma metabolite levels during OGTT did not significantly improve the diagnostic performance. CONCLUSIONS: Fasting plasma metabolome, but not change of plasma metabolome during OGTT, can improve the diagnosis of significant stenosis in patients with positive noninvasive stress test results.

Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data.

Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.

3Omics: a web-based systems biology tool for analysis, integration and visualization of human transcriptomic, proteomic and metabolomic data.

BACKGROUND: Integrative and comparative analyses of multiple transcriptomics, proteomics and metabolomics datasets require an intensive knowledge of tools and background concepts. Thus, it is challenging for users to perform such analyses, highlighting the need for a single tool for such purposes. The 3Omics one-click web tool was developed to visualize and rapidly integrate multiple human inter- or intra-transcriptomic, proteomic, and metabolomic data by combining five commonly used analyses: correlation networking, coexpression, phenotyping, pathway enrichment, and GO (Gene Ontology) enrichment. RESULTS: 3Omics generates inter-omic correlation networks to visualize relationships in data with respect to time or experimental conditions for all transcripts, proteins and metabolites. If only two of three omics datasets are input, then 3Omics supplements the missing transcript, protein or metabolite information related to the input data by text-mining the PubMed database. 3Omics' coexpression analysis assists in revealing functions shared among different omics datasets. 3Omics' phenotype analysis integrates Online Mendelian Inheritance in Man with available transcript or protein data. Pathway enrichment analysis on metabolomics data by 3Omics reveals enriched pathways in the KEGG/HumanCyc database. 3Omics performs statistical Gene Ontology-based functional enrichment analyses to display significantly overrepresented GO terms in transcriptomic experiments. Although the principal application of 3Omics is the integration of multiple omics datasets, it is also capable of analyzing individual omics datasets. The information obtained from the analyses of 3Omics in Case Studies 1 and 2 are also in accordance with comprehensive findings in the literature. CONCLUSIONS: 3Omics incorporates the advantages and functionality of existing software into a single platform, thereby simplifying data analysis and enabling the user to perform a one-click integrated analysis. Visualization and analysis results are downloadable for further user customization and analysis. The 3Omics software can be freely accessed at http://3omics.cmdm.tw.