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Original research article
Metabolomic analyses reveals new stage-specific features of the COVID-19
Hongling Jia, Chaowu Liu, Dantong Li, Qingsheng Huang, Dong Liu, Ying Zhang, Chang Ye, Di Zhou, Yang Wang, Yanlian Tan, Kuibiao Li, Fangqin Lin, Haiqing Zhang, Jingchao Lin, Yang Xu, Jingwen Liu, Qing Zeng, Jian Hong, Guobing Chen, Hao Zhang, Lingling Zheng, Xilong Deng, Changwen Ke, Yunfei Gao, Jun Fan, Biao Di, Huiying Liang
Please cite this article as: Jia H, Liu C, Li D, et al. Metabolomic analyses reveals new stage- specific features of the COVID-19. Eur Respir J 2021; in press (https://doi.org/10.1183/13993003.00284-2021).
This manuscript has recently been accepted for publication in the European Respiratory Journal. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online.
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Metabolomic analyses reveals new stage-specific features of the COVID-19
Hongling Jia1,2#, Chaowu Liu3#, Dantong Li15#, Qingsheng Huang4#, Dong Liu5#, Ying Zhang1#, Chang Ye4, Di Zhou6, Yang Wang6, Yanlian Tan2, Kuibiao Li1, Fangqin Lin4, Haiqing Zhang7, Jingchao Lin6, Yang Xu1, Jingwen Liu1, Qing Zeng1, Jian Hong8, Guobing Chen9, Hao Zhang10, Lingling Zheng4, Xilong Deng11, Changwen Ke12, YunfeiGao13,14,*, Jun Fan2,*, Biao Di1,*, HuiyingLiang15,16,*
Author Affiliations
1 Guangzhou Center for Disease Control and Prevention; Guangzhou, Guangdong Province, 510440; China 2 Department of Medical Biochemistry and Molecular Biology, School of Medicine, Jinan University; Guangzhou, Guangdong Province, 510632; China 3 Guangdong Institute of Microbiology, Guangdong Academy of Sciences; State Key Laboratory of Applied Microbiology Southern China; Guangzhou, Guangdong Province, 510632; China 4 Clinical Data Center, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University; Guangzhou, Guangdong Province, 510623; China 5 Big Data and Machine Learning Laboratory, Chongqing University of Technology; Chongqing, 400030; China 6 Metabo-Profile Biotechnology (Shanghai) Co. Ltd., Shanghai, 201315; China 7 Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, Hubei Province, 430030; China 8 Department of Pathophysiology, School of Medicine, Jinan University, Guangzhou, Guangdong Province, 510632; China 9 Institute of Geriatric Immunology, Department of Microbiology and Immunology, School of Medicine; Department of Neurology, Affiliated Huaqiao Hospital, Jinan University, Guangzhou, Guangdong Province, 510632; China 10 Institute of Precision Cancer Medicine and Pathology, School of Medicine, Jinan University, Guangzhou, Guangdong Province, 510632; China 11 Institute of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou, Guangdong Province, 510060; China 12 Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China 13 Zhuhai Precision Medical Center, Zhuhai People's Hospital (Zhuhai Hospital Affiliated with Jinan University), Jinan University; Zhuhai, Guangdong Province, 519000; China 14 The Biomedical Translational Research Institute, Jinan University Faculty of Medical Science, Jinan University; Guangzhou, Guangdong Province, 510632; China 15 Clinical Data Center, Guangdong Provincial People’s Hospital/Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, 510080; China 16 Lead Contact #These authors contributed equally to this study. *Address correspondence to:
Huiying Liang, MD, PhD (Email: [email protected])
Clinical Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, or Biao Di (Email: [email protected]); or Jun Fan (Email: [email protected]); or YunfeiGao (Email: [email protected]). Abstract
The current pandemic of coronavirus disease 19 (COVID-19) has affected more than 160 million of individuals and caused millions of deaths worldwide at least in part due to the unclarified pathophysiology of this disease. Therefore, identifying the underlying molecular mechanisms of COVID-19 is critical to overcome this pandemic. Metabolites mirror the disease progression of an individual by acquiring extensive insights into the pathophysiological significance during disease progression. We provide a comprehensive view of metabolic characterization of sera from COVID-19 patients at all stages using untargeted and targeted metabolomic analysis. As compared with the healthy controls, we observed different alteration patterns of circulating metabolites from the mild, severe and recovery stages, in both discovery cohort and validation cohort, which suggest that metabolic reprogramming of glucose metabolism and urea cycle are potential pathological mechanisms for COVID-19 progression.
Our findings suggest that targeting glucose metabolism and urea cycle may be a viable approach to fight against COVID-19 at various stages along the disease course. Introduction
Coronavirus disease 2019 (COVID-19), with its devastating consequences for the patients and their families, remains a major public health concern that has been posing an increasing financial and social burden worldwide [1, 2]. Notably, infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, may be asymptomatic or may result in a wide spectrum of clinical symptoms, ranging from mild acute febrile illness to moderate, clinically severe, and critical life-threatening infections [3-5]. This disease progression from mild to severe of COVID-19 are supposed to be driven by multi organ failure with specific metabolic alterations in patients. It is well known that viruses completely rely on their host's cell energy and metabolic resources for fueling the different stages of viral infection, such as enter, multiply, and exit for a new round of infection [6]. For certain respiratory tract viruses, the consequential development of hypoxia caused by lung function impairment may also alter metabolic profiles [7, 8]. The metabolite profiles of coronaviruses’ infection have been previously investigated by several research groups and they showed that levels of a series of small molecule metabolites, such as, free fatty acids, kynurenine, sphingolipids, glucose and amino acids, were altered as a result of virus infection, which were supposed to be involved in the changes of organ functions and immune responses [9, 10].
However, COVID-19genesis is a multistep process, samples collected from the severe patients or the mixed groups (including both mild or moderate, and severe type) were used in these investigations. Thus, the evidence of distinct stage-specific phenotypes of metabolite profiles caused by SARS-CoV-2 infection is still not fully understood.
In this study, a metabolomic analysis has been applied to screen metabolic variations, and further to figure out the comprehensive view of endogenous metabolites. Metabolomics approaches are generally classified as untargeted analysis or targeted analysis. The untargeted analysis is a relative-quantitative procedure that could maximally extracts the information of metabolites from the complex biological matrix without bias, whereas targeted quantitative metabolomics focuses on the detection of specific metabolites associated with some detailed class or metabolic pathways through the standard curve. We first analyzed the metabolic variations with untargeted approach, and then confirmed with targeted approach. Our further analysis showed that these altered metabolites are mainly involved in TCA cycle and Urea cycle pathway. More importantly, recovery group were included in our investigation. We obtained more valuable information about metabolic variations, through comparing recovery group with other groups.
Materials and methods
Study design and participants
From January to March, 2020, 63 adult COVID-19 patients who were confirmed at
Guangzhou Center for Disease Control and Prevention (CDC) laboratory and then were recruited and referred to the designated treatment center of Guangzhou for treatment. The diagnosis of COVID-19 was made following the Protocol for Novel Coronavirus Pneumonia
Diagnosis and Treatment issued by the National Health Commission of the People’s Republic of
China [11]. According to guidelines of Chinese Clinical Guidance For COVID-19 Pneumonia
Diagnosis and Treatment (Trial 6th version, table S1), patients were classified into three subgroups: 18 cases in mild group, 12 cases in severe group, and 20 cases in recovery group. For the prospective validation study, the other 93 COVID-19 patients who had been diagnosed with COVID-19 were independently enrolled. Of these 93 peripheral blood samples,
3 samples had to be excluded due to hemolysis, leaving us with the data of 90 patients for validation analysis.
During this same period, 13 and 28 healthy volunteers in discovery and validation cohort respectively, including 22 male and 19 female, were recruited at the Medical Examination
Center, No.8 People’s Hospital of Guangzhou with their ages ranging from 42 to 56 (mean 48).
Sample processing and clinical data collection
Blood samples of mild and severe group were collected at the time of diagnosis and when the patient's condition reached the severe standard, respectively. The time of sample collection of recovery group was that when COVID-19 test were negative for twice and isolation was released. Blood samples of healthy control were collected from the individuals who had annual physical examination during that period of time.
Peripheral blood samples were collected in vacuum negative pressure blood collection vessel. All subsequent processes were handled under Biosafety Level 3 containment conditions following risk assessments and code of practice approved by Guangdong CDC. Blood samples in serum separator tubes were centrifuged at 4°C at
1,500g for 10 min and serum aliquoted and stored at -80 °C until analysis.
Microsoft Excel (MS Excel 2013, version 15.0) is used for data collection on demographics and clinical information. Data on demographics, clinical presentations on admission, chest computed tomography (CT) scan and laboratory tests were collected. Laboratory data collected on each patient included complete blood count, urine and stool analysis, blood biochemistry, coagulation function, biomarkers of infection, as well as viral testing through nasopharyngeal.
Clinical data were obtained by reviewing clinical charts, nursing records, and results of laboratory testing and CT scan for all laboratory confirmed patients. The accuracy of the clinical data were confirmed by two pediatricians caring for the patients.
To explore whether SARS-CoV-2 infection could induce an intense infection response, we also tested three cytokines using samples from 4 groups by ELISA assay. The human TNF-a
(Cat:AD11069Hu), IL-1β (Cat: AD11042Hu) and IL-6 (Cat: AD10759Hu) ELISA kits were purchased from Beijing Andy Gene Co., Ltd. The concentrations of these three inflammatory biomarkers were determined according to the manufacturer’s protocols and absorbance was measured at 450 nm using a microplate reader. All samples were analyzed in triplicate and the average concentration for each patient was calculated.
Untargeted LC–MS/MS analysis
Untargeted analysis of serum samples was similar to that described previously with minor modifications [12]. 100 µL serum samples were extracted by adding 300 µL of precooled methanol and acetonitrile (2:1, v/v). After vortex for 1min and incubate at -20 °C for 2 hours, samples were centrifuged for 20 min at 4000 rpm. The supernatant was transferred into
Eppendorf tubes for vacuum freeze-drying. The metabolites were resuspended in 150 µL of 50% methanol and centrifuged for 30 min at 4000 rpm, and the supernatants were transferred to auto sampler vials for analysis. A quality control (QC) samples were prepared by pooling the same volume of each sample to evaluate the reproducibility of the analysis. The samples were performed on a system including Waters 2D UPLC (Waters, MA, USA), coupled to a Q-
Exactive mass spectrometer (Thermo Fisher Scientific, MA, USA) with a heated electrospray ionization (HESI) source and controlled by the Xcalibur 2.3 software program (Thermo Fisher
Scientific, MA, USA). Extracts were separated on a Waters ACQUITY UPLC BEH C18 column
(1.7 μm, 2.1 mm × 100 mm, Waters, USA). The column temperature was maintained at 45 °C. The mobile phase is consisted of 0.1% formic acid (A) and acetonitrile (B) in the positive mode, and is consisted of 10 mM ammonium formate (A) and acetonitrile (B) in the negative mode.
The separation was conducted through the following gradient: 0-1 min, 2% B; 1-9 min, 2%-98%
B; 9-12 min, 98% B; 12-12.1 min, 98% B to 2% B; and 12.1-15min, 2% B. The flow rate was
0.35 mL/min and the injection volume was 5 μL. The mass spectrometry parameters for positive/negative ionization modes were set as following: spray voltage, 3.8/−3.2 kV; sheath gas flow rate, 40 arbitrary units (arb); aux gas flow rate, 10 arb; aux gas heater temperature, 350 °C; capillary temperature, 320 °C.
The untargeted raw data (raw file) was imported into Compound Discoverer 3.0 (Thermo
Fisher Scientific, MA, USA) for data processing, including peak extraction, retention time correction within and between groups, additive ion pooling, missing value filling, background removal, and metabolite identification. Metabolite identification was conducted against the BGI reference Library (BGI inhouse-developed standard library), mzCloud (Thermo Fisher Scientific,
MA, USA), ChemSpider, Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Human
Metabolome Database (HMDB). Further, statistical analysis was performed on the resulting normalized peak intensities using metaX software [13]. There are multiple steps in metaX processing, including data quality assessment, missing value imputation, data normalization, univariate and multivariate statistics [14,15].
Targeted LC-MS/MS verification of identified metabolites
Targeted LC-MS/MS analysis was performed using an ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) system (ACQUITY
UPLC-Xevo TQ-S, Waters, MA, USA). 306 standards were obtained from Sigma-Aldrich (St.
Louis, MO, USA), Steraloids Inc. (Newport, RI, USA), and TRC Chemicals (Toronto, ON, Canada). All the standards were accurately weighed and prepared in an appropriate solution to obtain the individual stock solution at a concentration of 5.0 mg/mL. An appropriate amount of each stock solution was mixed to create stock calibration solutions. Serum samples were prepared and measured according to previously published method [16, 17, 18]. Briefly, an aliquot of 25μL of serum was added to a 96-well plate. 120μL ice cold methanol with internal standards was automatically added to each sample and vortexed for 5 minutes. Then the samples were centrifuged at 4000g for 30 minutes. 30μL of supernatant was transferred to a clean 96-well plate, and 20μL of derivative reagents was added to each well and the derivatization was carried out at 30°C for 60 min. After derivatization, 330μL of 50% methanol solution was added and then the plate was stored at -20°C for 20 minutes. Then the samples were centrifuged at 4000g at
4°C for 30 minutes. Finally, the supernatant wasused for LC-MS analysis.
The mobile phases consisted of 0.1% formic acid in water (mobile phase A) and acetonitrile-methanol (70:30, mobile phase B). 5 µL of each sample was injected onto an
ACQUITY BEH C18 column (1.7 µm, 100 mm × 2.1 mm) (Waters, MA, USA) maintained at 40
°C. The flow rate was 0.40 mL/min with the following mobile phase gradient: 0.0-1.0 min (5%
B), 1.0-11.0 min (5-78% B), 11.0-13.5 min (78−95% B), 13.5-14.0min (95−100% B), 14.0-16.0 min (100% B), 16.0-16.1 min (100-5% B), 16.1-18.0 min (5% B). The mass spectrometer was operated in the negative mode with a 2.0 kV capillary voltage and the positive mode with1.5 kV capillary voltage. The source and desolvation temperatures were 150°C and 550 °C, respectively.
The targeted raw data were processed through calibration curve of standards. The calibration curve was analyzed by instrument response and standards concentration. Then, the targeted metabolites were analyzed by the iMAP software (v1.0, Metabo-profile, Shanghai,
China). The Orthogonal Partial Least Square Discriminant Analysis (OPLS-DA) was used to maximize identification of differences in metabolic profiles between groups. In addition to the multivariate statistical method, the Student’t test or Wilcoxon’s rank-sum test was also applied to estimate the significance of each metabolite. The P values across all metabolites within each comparison were adjusted by a false discovery rate method. Finally, the significantly differential metabolites need to meet the following criteria: ①VIP>1; ②log2FC>0.25 or <-0.25;
③FDR<0.05.
Statistical analysis
All data were analyzed with R (v3.5.0) and differential metabolomic analysis was performed with
MSstats R package which includes log2 transformation, normalization and P-value calculation on the
Spectronaut and skyline quantitative data. The clustering algorithm used Hierarchical Cluster
(HCA)with hcaMethods R package, and the distance calculation was performed in Euclidean distance with the heatmap-package in R software to reveal the relationship between samples and metabolites. KEGG pathway enrichment analysis of differential metabolites was performed with the KEGG database (v89.1) using Fisher's exact test by comparison with all the identified metabolites. Correlation analysis was performed using pearson correlation coefficient analysis with corrplot R package.
Categorical variables were summarized in percentage and compared between different groups using χ² test or Fisher’s exact test. Continuous variables were expressed as the mean and
95% confidential interval (95%CI) or the median and inter quartile range (IQR), whichever deemed appropriate. For the multiple comparison of the four independent groups, the raw values of each metabolite were selected and normalized to the control group respectively. The Tukey's range test was conducted for all
11 metabolites, and the significance level for the test, alpha value, were set to 0.5. To verify whether the identified metabolites could be used as potential predictors for classification of
different stage groups, logistic regression model with 5-fold cross-validation approach was designed and
performed to predict the reliability and failure rate. All possible combinations containing N metabolites (N=1,
2, 3,...,9) were exhaustively tested by the model, and the predictive power of each combination was recorded
and ranked according to the Area-Under- Curve (AUC) value by receiver operating characteristic (ROC)
analysis. To ensure a large enough sample size, all corresponding AUC were calculated for discovery cohort
and validation cohort as a whole, and presented as specific or average value.
Data and materials availability
This study did not generate new unique reagents. Untargeted and targeted metabolomics datasets are deposited into the public Mendeley database.
(https://data.mendeley.com/datasets/pcdgvmg9ws/
draft?a=68f3ffb1-077e-47bc-945d-c9207cdc1c71)
Study approval
The study protocol for patient and healthy volunteer recruitment and sampling was approved
by the Ethical Committee of Guangzhou CDC with reference number (GZCDC-ECHR-
2020A0002).
Results
Untargeted metabolomic profiling of sera from all-stage of COVID-19 patients
To determine the alterations in circulating metabolites from COVID-19 patients, we applied
untargeted metabolomic analysis in the discovery cohort including 13 healthy subjects as normal
group, 18 mild patients, 12 severe cases, and 20 individuals recovery from severe scenario of
COVID-19. Clinical signs and symptoms, together with the laboratory parameters of patients that
infected with COVID-19 were collected and analyzed (table 1). Compared to mild group, patients in severe group showed significant suppression of lymphocyte, but increase of leucocytes and AST, indicating the disturbance of immune system and liver function.
Table 1. Characteristics of discovery cohort patients infected with COVID-19 at admission, according to disease severity
Characteristics Mild (n=18) Recovery (n=20) Severe (n=12) P
Age (years) 50.67(43.89-57.44) 50.20(42.05-58.35) 65.33(58.76-71.90) 0.013
Gender
Male 9(50.0%) 12(60.0%) 7(58.3%) 0.811
Female 9(50.0%) 8(40.0%) 5(41.7%)
Coexisting disorder* 11(61.1%) 7(35.0%) 5(41.6%) 0.257
Clinical signs and symptoms
Fever 16(88.9%) 12(60.0%) 10(83.3%) 0.091
Cough 14(77.8%) 11(55.0%) 7(58.3%) 0.308
Chilly 5(27.8%) 4(20.0%) 0(0.0%) 0.146
Myalgia 7(38.9%) 1(5.0%) 0(0.0%) 0.004
Fatigue 11(61.1%) 0(0.0%) 2(16.7%) <0.001
Rhinorrhoea 4(22.2%) 1(5.0%) 0(0.0%) 0.087
Shortness of breath 2(11.1%) 0(0.0%) 10(83.3%) <0.001
Sore throat 5(27.8%) 0(0.0%) 1(8.3%) 0.028
Diarrhea 0(0.0%) 1(5.0%) 0(0.0%) 0.465
Chest CT findings
Ground-glass opacity 8(44.4%) 15(75.0%) 11(100.0%) 0.005
Local mottling shadow 2(11.1%) 2(10.0%) 0(0.0%) 0.499
Bilateral mottling shadow 9(50.0%) 5(25.0%) 3(25.0%) 0.201
Laboratory parameters
Leucocytes(×10⁹/L; NR:3.5-9.5) 5.50(4.28-6.72) 5.26(4.54-5.98) 9.32(7.48-11.17) <0.001
Lymphocytes(×10⁹/L; NR:1.1-3.2) 1.59(1.13-2.06) 1.39(1.13-1.64) 0.45(0.30-0.60) <0.001 Neutrophils(×10⁹/L; NR:1.8-6.3) 3.65(2.51-4.80) 3.35(2.80-3.90) NA 0.605
Platelets(×10⁹/L; NR:125.0-350.0) 198.28(169.52-227.04) 184.30(153.83-214.77) 181.94(137.44-226.43) 0.723
HGB(g/L; NR:130.0-175.0) 127.48(111.08-143.89) 135.67(120.24-151.10) 108.24 (95.03-121.46) 0.096
APTT(s; NR:21.0-37.0) 38.93(36.80-41.05) 39.73(37.68-41.77) NA 0.574
PT(s; NR:10.5-13.5) 13.84(13.41-14.27) 14.26(13.36-15.16) NA 0.399
D-dimer(mg/L; NR:0-500) 1833.9(240.8-3427.0) 1827.0(976.4-2677.6) NA 0.993
Albumin (g/L; NR:40.0-55.0) 39.10(36.17-41.99) 39.51(36.89-42.13) 33.52(28.93-38.10) 0.033
ALT (U/L; NR:9.0-50.0) 30.93(21.67-40.19) 26.25(17.74-34.76) 95.75(27.53-163.96) <0.001
AST (U/L; NR:15.0-40.0) 26.82(16.35-37.30) 24.47(20.36-28.58) NA 0.650
TB (μmol/L; NR:0.0-21.0) 14.44(9.87-19.02) 11.01(7.72-14.31) 24.95(9.40-40.49) 0.014
BUN (mmol/L; NR:3.6-9.5) 4.43(3.14-5.71) 4.52(3.48-5.56) NA 0.904
Scr (μmol/L; NR:57.0-111.0) 59.68(53.15-66.22) 78.68(58.42-98.95) NA 0.075
CK (U/L; NR:50.0-310.0) 67.83(47.14-88.53) 81.95(52.77-111.13) NA 0.423
LDH (U/L; NR:120.0-250.0) 217.89(162.28-273.50) 210.35(176.99-243.71) NA 0.804
CRP (mg/L; NR:0.0-5.0) 19.10(11.66-26.53) 20.50(12.45-28.55) 9.25(6.59-11.92) 0.157
Abbreviation: HGB, hemoglobin; APTT, activated partial thromboplastin time; PT, prothrombin time; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TB, total bilirubin; BUN, blood urea nitrogen; Scr, serum creatinine; CK, creatine kinase; LDH, lactate dehydrogenase; CRP, C-reactive protein; NA, not available; NR, normal reference. *Including hypertension, type 2 diabetes mellitus, cancer, hyperlipidemia, liver disease and other chronic diseases.
All serum samples were processed and analyzed through UPLC-MS/MS for untargeted
metabolomics following the standardized protocol. Hydrophilic and hydrophobic molecules were
analyzed using both of positive and negative ionization to cover various endogenous biochemical
classes. Totally, 2466 metabolite peaks representing 631 and 1835 differential metabolites in
negative and positive ion modes were identified in the untargeted metabolomics analysis. With
coefficients of relative standard deviation <0.30 across quality control samples, 240 metabolites were identified based on MS/MS spectra through BGI reference Library, MzCloud, KEGG and
HMDB (table S2). From the principal component analysis (PCA), the data from quality control
(QC) set showed consistency and reproducibility (figure 1B). It was noteworthy that the metabolites of the mild group were partially coincident with normal group, while severe group and recovery group were easily distinguished (figure 1B, figure S1). 193 out of 240 metabolites were significantly associated with COVID-19 (FDR<0.05, figure 1C). Compared to the normal group, the volcano plots showed that there were 48 metabolites in mild group significantly increased and 33 decreased while 59 increased and 29 decreased in severe group, and the number was even greater in recovery group with 64 went up and 34 went down (figure 1D, FDR<0.05,
Log2FC>0.25 or <-0.25, VIP>1). Among these significant metabolites, numerous amino acids such as glutamine, glutamate, arginine, ornithine, kynurenine, tryptophan were correlated with disease severity. And some metabolites like glucose, lactate, pyruvate, participating in TCA cycle, showed disorder with the progression of COVID-19. These results suggest that the metabolites involved in the pathways like nitrogen metabolism, TCA cycle, fatty acid metabolism were imbalanced during progression of COVID-19 (figure S2).
Targeted metabolomic revealed alterative metabolites in all-stage of COVID-19 patients
To further quantify the changes of circulating metabolites between those four groups, we performed the targeted metabolomics analysis by Q300 Kit (Metabo-Profile, Shanghai, China).
Q300 Kit is the most comprehensive kit for analysis of targeted metabolic profiling. With coverage of up to 306 metabolites and more than 12 biochemical classes, the kit not only includes the differential metabolites detected by untargeted screening like glutamine, arginine, ornithine, glucose, lactate, pyruvate, but also contains other metabolites such as indoles, bile acids, and short-chain fatty acids, etc. These metabolites involved in nitrogen metabolism, TCA cycle, fatty acid metabolism, amino acid metabolism, and bile acid metabolism, etc.
In this study, we first quantified serum metabolites from 59 subjects (discovery cohort, 4 samples were excluded due to less volume). Based on the concentrations presented in different groups, totally 199 metabolites were divided into 16 clusters (figure S3, table S3). Then we classified these clusters into three groups, according to whether the metabolites return to normal level in recovery group (figures S3, A-C). Concentration of metabolites in figure S3-C returned to nearly normal level while those in figure S3-A and S3-B still showed substantial differences in contrast to normal levels. Concentrations of metabolites in figure S3-A increased as the disease progressed, and maintained at relatively higher level in recovery group. Concentrations of metabolites in figure S3B were found to decrease as the disease developed, but did not return to normal levels.
We compared the metabolomic profiling of various stages of COVID-19 to healthy group to identify and characterize specific metabolites and metabolic pathways involving the progression of COVID-19. We focused on the difference between the various stages of COVID-19 with normal group. A significance threshold of 0.5 was generally adopted for Q2 and R2 in OPLS-DA model [19, 20, 21]. Clear differences were found for the following groups: normal versus mild, cumulative R2Y=0.941 and Q2Y=0.783; normal versus severe, R2Y=0.955 and Q2Y=0.79; normal versus recovery, R2Y=0.926 and Q2Y=0.815 (figure S4). Furthermore, we quantified serum metabolites from another 118 subjects as an independent validation (for demographic characteristics, see table S4). The same model was adopted, and the results showed high consistency, which were presented in figure S5.
Alteration of main metabolites across different stages 80 out of 199 metabolites quantified in the targeted metabolomics showed significant differences (FDR<0.05, table S5) in at least one of the stages compared to the normal group
(figure 2-A). Pathway analysis by SMPDB and KEGG showed that aspartate metabolism, urea cycle, arginine and proline metabolism, glycine and serine metabolism, and TCA cycle were disordered (figure 2-B, figure S6-A and -B). In particular, arginine and ornithine presented with a remarkable decrease or increase (figure 2-B, figure 6), both of which were crucial components in urea cycle. The influences on TCA cycle, pyruvate metabolism and glycolysis merged to indicate the disturbance of energy metabolism, which was supported by the extreme high level of lactate in severe group. This might be due to that patients still could not obtain the oxygen effectively and the nutrition might also get affected, even with the respiratory support, thus created a huge obstacle for energy metabolism. This phenomenon could also be found in the patients who went through severe scenario into recovery group, indicating that a full recovery had not been achieved even with the COVID-19 nucleic acid test negative. In other words, even if SARS-CoV-2 were completely removed, the damage still exists for some time, or long time.
Changes in the metabolite abundances in all four groups were shown in the pathway representation (figure 2-B).
Dysregulated urea cycle and TCA cycle in disease progression
The urea cycle and TCA cycle responsible for amino acid metabolism and energy metabolism were ranked as the top 2 affected metabolic pathways according to the analysis
(figure 3). 11 metabolites that belong to or are closely related to the two cycles, were observed with significant changes among different groups (figure 3, table S6) in the discovery cohort.
Furthermore, 9 out of the 11 metabolites were testified with significant changes among different groups (figure 3, table S7). These 9 metabolites were creatine, arginine, ornithine, asparate, pyruvate, malate, citrulline, glutamine and 2-oxoglutarate. Focused analysis highlighted significant increases of 2-oxoglutarate, asparate and ornithine levels, compared to normal group. Malate and 2-oxoglutarate presented with the highest level in severe group, indicating that TCA cycle got seriously affected. Ornithine, which plays the key role in urea cycle, increased consistently and reached the highest level in the recovery group. In contrast, the level of arginine, another vital amino acid in urea cycle, decreased significantly in severe group compared to that in normal group, suggesting the dysregulation of urea cycle during the
COVID-19 progression.
Combination of sera metabolites may be a potential predictive biomarker
To study if the nine metabolites could be used as biomarker to risk stratify COVID-19 patients, several classic models were trained with the discovery cohort and validated with the validation cohort including decision trees (figure S7), random forest (figure S8), support vector machine (SVM) (figure S9), and logistic regression (figure S10). We adopt logistic regression for its better performance. The mean AUC for logistic regression using 3, 5, and 7 metabolites in validation cohort were presented in figure S11. Using different combinations of the above 9 metabolites and the whole study participant’s data (discovery cohort + validation cohort), we found that the more metabolites involved, the higher classification value observed of all distinguish between any two groups (figure 4A-F). However, the alteration pattern of circulating metabolites was different during the disease progression. For example, when we applied fewer metabolites, the model can distinguish “severe” from “normal” with relatively higher accuracy, but not for "mild" from “normal” (figure 4-G). When the number of metabolites increased, the accuracy of the model distinguishing mild from severe was improved (figure 4G-I). Furthermore, relatively higher AUC value to distinguish “recovery” from “normal” also suggests that subjects who survived the severe scenario might still suffer from long-lasting collateral damage regarding to metabolic conditions. For further exploration, we performed logistic regression using 9 metabolites individually in discovery, validation and the combined cohorts and found that creatine, 2-oxoglutarate and pyruvate maintained passing performance in three cohorts (figure
S12), leading to the potential for the metabolites to serve as predictive biomarkers. To better validate our findings, we compared the 9 metabolites with the results of Shen et. al. [9] and found 4 metabolites that overlapped: malate, pyruvate, citrulline and glutamine. We then built logistic regression model using these 4 metabolites as features and trained with both discovery and validation cohort. The model was then validated utilizing the published results from Shen et. al. paper data and achieved good performance in distinguishing severe and normal (figure S13), proving the model could hold up across studies. Such results indicated that malate, pyruvate, citrulline and glutamine might serve as potential biomarkers to risk stratify COVID-19 severe patients.
Discussion
Our present study for the first time systematically provides a comprehensive view of metabolic characterization of sera from COVID-19 patients at all stages, especially including the recovery stage of the disease course. Targeted and untargeted metabolomic profiling of sera from
COVID-19 patients identified different alteration patterns of circulating metabolites from the mild, severe and recovery stages. Most individuals who acquire the SARS-CoV-2 infection experience mild disease, whereas some of them progress to severe or critical disease. These severe/critical and recovery cases are driven by the host responses to the infection, and thus result in multisystem dysfunction and pathology. Comprehensive analysis of circulating metabolites from COVID-19 patients at all stages would help us develop comprehensive strategy to better treat this disease.
We identified circulating metabolites, including malate, 2-oxoglutaratek and asparate, which were increased compared to normal level, suggesting that the dysregulated glucose metabolism and TCA cycle could be crucial in susceptibility, severity and recovery during COVID-19 disease course. Glucose either goes through aerobic metabolism and provides energy for diverse biological processes or oxidized through pentose phosphate pathway to yield nicotinamide adenine dinucleotide phosphate (NADPH) to maintain redox homeostasis, which involves in host immune responses to against pathogenic microorganisms under aerobic condition. While under anaerobic condition, which is most common in COVID-19 patients, glucose goes through glycolysis and is fermented to lactate with limited amount of ATP production, and causes the elevated blood lactate and LDH levels [22, 23]. Our finding indicates that, in addition to anaerobic glycolysis, which usually occurs in most COVID-19 patients, TCA cycle was also enhanced during all stages of the disease. We proposed that SARS-CoV-2 viruses hijack the host machinery, including glucose metabolism, to promote pathogenesis of COVID-19.
Infection with SARS-CoV-2 of Caco-2 cells was reported to upregulate glucose metabolism and block glycolysis with non-toxic concentrations of 2-deoxy-d-glucose (2-DG) to prevented
SARS-CoV-2 replication [24]. SARS-CoV-2 viruses in infected cells consumed large amount of cellular ATP to support the viral replication as high ATP concentration promoted the translocation of SARS-CoV in the unwinding of duplex RNA, which is required for viral replication [25]. Type I IFNs (IFN-I) is major components of the innate immune system and represents critical antiviral molecules [26, 27]. Viral infection causes the host to activate an antiviral response that, in part, is dependent on mitochondrial antiviral signaling protein (MAVS) to produce type I interferons. Cell model and animal model of SARS-CoV-2 infection, in addition to transcriptional and serum profiling of COVID-19 patients, consistently revealed a unique and inappropriate inflammatory response. This response is defined by low levels of type I and type
III interferons juxtaposed to elevated chemokines and high expression of IL-6. Reduced innate antiviral defenses coupled with exuberant inflammatory cytokine production are the defining and driving features of COVID-19 [28]. In order to show the inflammation marker changes in our cohort, we also selected 18 samples with sufficient volume from each group to examined IL-6,
TNF-α and IL-1β level, which were showed to be involved in COVID-19 infection. Our results showed that IL-1β level was higher in mild stage, and was the highest in severe stage, compared with control. But it was much lower in recovery stage, although still higher than that in control group (figure S14-A). IL-6 and TNF-α had the same trends (figure S14-B and -C). These results gave us the clue that inflammation level was closely related with COVID-19 disease development and might be involved in the production of metabolites. We therefore further conducted correlation analysis and found that the level of asparate, creatine, malate, and 2- oxoglutarate were positively correlated with the expression of cytokines (figure S15). Clinical study showed that patients with no IFN-production presented poorer outcome, and all of them required invasive ventilation and longer intensive care unit stay. The viral load tended to be higher in IFN-negative patients with COVID-19 at disease diagnosis [29].
In our study, dysregulated urea cycle with decreased arginine and increased ornithine was also identified in the sera of COVID-19 patients, suggesting metabolic reprogramming may be involved in COVID-19 disease progress. Another example showing the metabolic reprogramming in antiviral response came from a mouse model of virus infection. Type I interferon was found to alter the expression and function of key enzymes of the urea cycle in hepatocytes, result in decreased arginine and increased ornithine concentrations in the circulation and suppress virus-specific CD8+ T cell responses [30, 31, 32]. However, whether type I interferon also regulates urea cycle in alveolar epithelial cells during SARS-COV-2 infection is an important question, and remains to be investigated.
In our dataset, the level of arginine significantly decreased in sera of COVID-19 patients compared to that in healthy control group, which was consistent to the findings from other teams
[33]. It is well known that arginine can either be converted to ornithine and urea using enzyme arginase or to nitric oxide and citrulline through enzyme nitric oxide synthase [34]. Nitric oxide or its derivatives was reported to affect the fusion between the S protein of SARS-CoV and its cognate receptor, angiotensin converting enzyme 2, and reduce viral RNA production in the early steps of viral replication [35]. The effect of nitric oxide as a potential treatment on COVID-
19 is well recognized, and a phase 3 clinical study (PULSE-CVD19-001) of inhaled nitric oxide
(iNO) therapy in up to 500 patients infected with COVID-19 was approved by FDA in May
2020. Decreased level of arginine with increased concentration of ornithine but decreased production of ornithine in the sera of COVID-19 patients from our finding suggests that the conversion of arginine to ornithine in urea cycle is dominant compared to that of arginine to ornithine in NO cycle in COVID-19 patients. It would be interesting to investigate whether
SARS-COV-2 infection reduce nitric oxide production to keep viral replication by switching the metabolic route to urea cycle. In addition to our findings of changes of urea cycle and glucose metabolism in COVID-19,
Shen et. al. uncovered dysregulated metabolites in lipid metabolism, suggesting their significant regulation in signal transduction and immune activation process [9]. Kimhofer et al. also determined the metabolic effects of severe acute respiratory syndrome coronavirus 2 (SARS-
CoV-2) infection on human blood plasma using multiplatform metabolic phenotyping. They also observed key discriminant metabolites including elevated α-1-acid glycoprotein and an increased kynurenine/ tryptophan ratio in COVID-19 patients, indicating that liver dysfunction was one of the potential pathological mechanisms [31]. In another study on plasma metabolomic and lipidomic alterations associated with COVID-19, carbamoyl phosphatase, which participates in the urea cycle, was shown to be reduced in patients [36]. This finding is particularly consistent with our finding that the level of citrulline, which is formed from carbamoyl phosphate, was significantly downregulated in mild and severe patients. These data collectively indicated that the dysregulated urea cycle was involved in the potential pathological mechanisms of COVID-19 disease progression. Chiara Bruzzone et. al. [32] revealed abnormally high levels of ketone bodies and 2-hydroxybutyric acid, a readout of hepatic glutathione synthesis and marker of oxidative stress in COVID-19 patients, which suggested SARS-CoV-2 infection induced liver damage associated with dyslipidemia and oxidative stress. Denisa Bojkova1 et. al. established a human cell-culture model for infection with a clinical isolated SARS-CoV-2 and determined the infection profiling of SARS-CoV-2 by translatome and proteome proteomics. They revealed the reshape of SARS-CoV-2 in central cellular pathways, including carbon metabolism and nucleic acid metabolism. Their findings further enabled the identification of drugs that inhibit viral replication by targeting these pathways [24]. Shen B et al compared proteomic and metabolomic profiling of sera from COVID-19 patients with that from control individuals. They identified molecular changes, which implicated dysregulation of macrophage, platelet degranulation, complement system pathways, and massive metabolic suppression, and might be useful to screen the potential blood biomarkers for severity evaluation [9]. Seriously ill COVID-19 patients are technically afflicted with sepsis, which involves life-threatening organ dysfunction caused by a person's dysregulated immune response to an infection. Our dysregulated metabolite data also showed considerable overlap with previous studies, suggesting the underlying relationship between dysregulated metabolic pathways and development of sepsis [37-40]. Generally speaking, elucidation of the full spectrum of pathophysiological mechanisms, how these metabolic reprogramming can be targeted and providing a “proof of principle” for COVID-19 treatment will be important in further investigations.
Although we successfully recruited 63 and 118 patients for the discovery and validation cohort, respectively, the cohorts were still relatively in small size to obtain the best reliability. To confirm our findings, metabolic analysis of serum sample from a larger scale of COVID-19 cohorts maybe warranted. However, high consistency of the results from the validation cohort and the discovery cohort further consolidated our results. In addition, the cohorts had some important parameters that were not matched. For example, severe cases often occurred in the elderly. Although there were no significant differences among control group, mild group, and recovery group, it did create a natural mismatch between mild or recovery group and severe group, which should be taken into account when interpreting results.
Taken together, our metabolomic data presented here provided a comprehensive view of circulating metabolite characterization from COVID-19 patients at all stages and identified metabolic reprogramming of glucose metabolism and urea cycle as potential pathological mechanisms of COVID-19. Targeting host metabolism might be a viable approach to fight against COVID-19 at various stages along the disease course [41]. Acknowledgments
We thank all patients and healthy individuals involved in this study, as well as the dedicated medical and research staffs, who fight against SARS-CoV-2 worldwide. We thank Jinling Tang for editing the manuscript. Funding: This work was supported by The Key Project of Medicine
Discipline of Guangzhou (2021–2023-11), Basic Research Project of Key Laboratory of
Guangzhou (202102100001).
Author Contributions
H.L, J.F., H.J., and B.D. conceived, designed and supervised the study. Y.Z., K.L., Y.X.,
J.L., Q.Z. and X.D. collected clinical samples. Y.W., D.Z., J.L. and C.K. performed the experiments. C.L., D.Z., Y.W., Y.T, J.H., G.C. and H.Z. conducted the data analysis. D.L., C.Y.,
Q.H., D.L., H.Z., F.L. and L.Z. performed mapping. Y.G., J.F., H.J., D.L. and H.L. accomplished manuscript writing. All authors read and approved the final manuscript.
Declaration of Interests
The authors declare no competing interests.
Figure Legends
Figure 1. Untargeted metabolomic profiling of sera from COVID-19 patients at all stages in the discovery cohort.
Untargeted metabolomic analyses were performed using sera from healthy control (normal) group and patients of mild, severe and recovery group.(A) Schematic diagram of the study design;(B) Principal component analysis (PCA) of untargeted metabolomics among four groups;(C) Heatmap of selected 193 metabolites with FDR<0.05;(D) Volcano plots highlighted the serum metabolites that increased (red) or decreased (blue) in mild, severe, and recovery groups, as compared to normal group, with FDR<0.05, Log FC>0.25 or <-0.25, OPLS-DA VIP>1. 2 Figure 2. Alteration of main metabolisms in sera from the discovery cohort among different stages
(A) Heatmap of metabolites quantified in targeted metabolomics with FDR<0.05; (B) Pathway analysis identified significant difference in amino acids metabolism, especially regarding arginine, ornithine and glutamine, together with energy metabolism including TCA cycle and glycolysis. Each box in a pathway represented a metabolite, and was marked in red if found in targeted metabolomics or in yellow for untargeted metabolomics. Bar plots showed averaged absolute concentration of metabolites of normal, mild, severe, recover stages (from left to right). Green stand for organic acids; orange for amino acids; purple for carbohydrates and blue for short chain fatty acids.
Figure 3. Dysregulation of urea cycle and TCA cycle might be involved in the pathological progression
An overview of metabolites closely related to the urea cycle and TCA cycle. Boxplots showed levels of these metabolites in discovery and validation samples among different stages. Metabolomics pathway analysis in both discovery cohort and validation cohort identified that urea cycle and TCA cycle as the top two pathways affected in patients with COVID-19. Asterisks indicated statistical significance, p value: *, <0.05; **, <0.01; ***, <0.001. The colors in box plots represented different stages: blue for normal; orange, mild; red, severe; and yellow for recovery.
Figure 4. AUC of models by combination of 9 significantly changed metabolites in the urea cycle and TCA cycle
Nine metabolites were used as features to build logistic regression models. (A-F) The scatter plots of AUC in distinguishing different stages using 1-9 metabolites. X-axis showed the numbers of the metabolites used in the model. Models by all possible combinations were built, and each point showed the AUC of one single combination. The plots showed that models achieved better performance with the number increased. By combining 3metabolites, most models’ AUC>0.90 for Severe-vs-Normal. By combining 5 metabolites, most models’ AUC > 0.90 in all group pairs. By combining 7 metabolites, all models’ AUC>0.90in all group pairs. (G-I) Mean AUC plots for models using 3, 5, and 7 metabolites. The mean AUC of models by all possible combination with 3, 5 and 7 metabolites were calculated separately. The nine metabolites included creatine, arginine, ornithine, asparate, pyruvate, malate, citrulline, glutamine and 2-oxoglutarate. References
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Figure S1. Untargeted metabolism analyses were performed using sera obtained from subjects of different stages: normal, mild, severe, and recovery. (A) OPLS-
DA score plots for mild, severe and recovery group, compared to normal group. (B)
999 permutation tests to evaluate the quality of the OPLS-DA model.
Figure S2. 193 selected metabolites in the discovery cohort by untargeted metabolomics were classified and presented in the heatmap (related to figure 1-C).
Figure S3. Targeted metabolomic analysis revealed different trends of metabolites in the discovery cohort among different stages. Targeted metabolomic analysis quantified 199 metabolites from sera of the four groups and the data were clustered into
16 discrete clusters using mFuzz, to illustrate the relative expression changes in different groups. All 199 metabolites and the respective cluster of each were listed in table S4. Five metabolites of each cluster were randomly selected and listed at the upper right corner. The 16 clusters were classified into three groups, according to the level of metabolites in recovery groups: (A) higher than normal; (B) lower than normal; (C) on par with normal. The characters on X axis represented different groups: N: Normal; M:
Mild; S: Severe; R: Recovery.
Figure S4. Targeted metabolomic analyses were performed using sera obtained from the discovery cohort. (A) Volcano plots highlighted differential metabolites of subjects in mild, severe and recovery groups, compared to normal group. (B) OPLS- DA score plots for mild, severe and recovery group, compared to normal group. (C)
999 permutation tests to evaluate the quality of the OPLS-DA model.
Figure S5. Targeted metabolomic analyses were performed using sera obtained from the validation cohort. (A) Volcano plots highlighted differential metabolites of subjects in mild, severe and recovery groups, compared to normal group. (B) OPLS-
DA score plots for mild, severe and recovery group, compared to normal group. (C)
999 permutation tests to evaluate the quality of the OPLS-DA model.
Figure S6. Pathway enrichment analysis of the discovery cohort by targeted metabolomics using SMPDB (A) or KEGG (B) (related to figure 2).
Figure S7. The scatter plots of AUC in distinguishing different stages using 1-9 metabolites in decision tree.
Figure S8. The scatter plots of AUC in distinguishing different stages using 1-9 metabolites in random forest.
Figure S9. The scatter plots of AUC in distinguishing different stages using 1-9 metabolites in support vector machine.
Figure S10. The scatter plots of AUC in distinguishing different stages using 1-9 metabolites in logistic regression.
Figure S11. Mean AUC for logistic regression using 1, 3, 5, and 7 metabolites.
Figure S12. The pooled AUC for the prediction accuracy of disease status using metabolite biomarkers.
Figure S13. AUC of logistic regression model validated using data in Shen et.al. paper
Figure S14. Level of IL-1β, TNF-α and IL-6 detected in sera of different groups in the validation cohort. (A) showed IL-1β. (B) and (C) showed TNF-α, IL-6 respectively.
Figure S15. Correlation analysis of the 9 metabolites versus 3 cytokines for patients in normal, mild, severe and recovery group. Among 9 metabolites, asparate was found positively correlated with TNF-α while malate and creatine correlated with
IL-6 and IL-1β. 2-oxoglutarate was found to have positive correlations with all three cytokines. The result was obtained by Pearson correlation coefficient analysis.
Table S1. Definitions of clinical types of COVID-19 in adult patients
Mild • Upper respiratory symptoms (eg, pharyngeal congestion, sore throat, and fever) for a short duration or asymptomatic infection • Positive RT-PCR test for SARS-CoV-2 • No abnormal radiographic and septic presentation Moderate • Imaging shows pneumonia. • Symptoms such as fever, cough, fatigue, headache, and myalgia Severe Mild or moderate clinical features, plus any manifestations that suggest disease progression: • Respiratory distress, breathing frequency ≥30 times/minute; • In the resting state, it means oxygen saturation ≤93%; • Arterial blood oxygen partial pressure (PaO₂ )/oxygen concentration (FiO₂ )≤300 mmHg (1 mmHg = 0.133kPa).
Critical Rapid disease progression, plus any other conditions: • Respiratory failure with need for mechanical ventilation (eg, ARDS, persistent hypoxia that cannot be alleviated by inhalation through nasal catheters or masks) • Septic shock • Organ failure that needs monitoring in the ICU
COVID-19=coronavirus disease 2019. SARS-CoV-2=severe acute respiratory syndrome coronavirus 2. ARDS=acute respiratory distress syndrome. ICU=intensive care unit. Table S2. Metabolites detected in the discovery cohort by untargeted metabolomics Normal VS Mild Normal VS Severe Normal VS Recovery Total Class Name HMDB_ID KEGG_ID P FDR log2FC VIP P FDR log2FC VIP P FDR log2FC VIP P FDR Others 1-methyladenosine HMDB0003331 C02494 <0.001 <0.001 0.91 1.7671 <0.001 0.001 0.72 1.417 <0.001 <0.001 -1.29 1.5723 <0.001 <0.001 Amino acids N-acetyl-l-leucine HMDB0011756 C02710 <0.001 <0.001 2.482 2.1962 <0.001 <0.001 0.933 1.417 0.0049 0.009 -0.37 0.1649 <0.001 <0.001 Amino acids N-acetyl-l-phenylalanine HMDB0000512 C03519 <0.001 <0.001 3.14 2.1249 <0.001 0.002 1.87 1.4 <0.001 <0.001 -0.73 0.1835 <0.001 <0.001 Amino acids N-acetylproline HMDB0094701 - <0.001 <0.001 2.223 1.8915 0.611 0.7068 0.277 0.916 0.0177 0.030 -0.16 0.2193 <0.001 <0.001 Amino acids 2-phenylglycine HMDB0002210 - <0.001 <0.001 2.68 0.6317 0.003 0.009 2.50 0.983 <0.001 <0.001 0.90 0.3909 <0.001 <0.001 Amino acids Creatinine HMDB0000562 C00791 0.6377 0.71101 0.06 0.1746 0.005 0.0138 -0.43 1.174 0.0025 0.005 0.27 0.6989 <0.001 <0.001 Amino acids N-acetyl-l-alanine HMDB0000766 - 0.417 0.518 0.06 0.5434 0.0114 0.025 0.18 1.18 <0.001 <0.001 0.50 0.7862 <0.001 <0.001 Amino acids Nicotinuric acid HMDB0003269 C05380 0.65 0.71609 -0.08 0.1592 <0.001 0.0012 1.543 1.062 0.0016 0.003 0.65 0.8255 <0.001 <0.001 Amino acids Dl-tryptophan HMDB0030396 C00806 0.045 0.089 -0.22 0.8762 0.0701 0.122 -0.30 0.73 0.0133 0.023 0.26 0.8387 <0.001 <0.001 Amino acids Levothyroxine HMDB0000248 C01829 0.0586 0.11279 0.228 0.7975 0.005 0.0137 -0.59 1.24 0.001 0.002 0.40 0.9823 <0.001 <0.001 Amino acids L-allo-threonine HMDB0004041 C05519 0.003 0.010 -0.54 1.2911 0.0298 0.056 -0.40 0.786 0.0033 0.006 0.41 0.9895 <0.001 <0.001 Amino acids 2-hydroxyphenylalanine HMDB0006050 - 0.2258 0.31431 -0.96 0.1838 0.110 0.1715 -1.08 0.432 <0.001 <0.001 -2.15 1.1783 <0.001 <0.001 Amino acids Leucyl proline HMDB0011175 - 0.177 0.267 0.33 0.5544 <0.001 <0.001 1.17 1.32 <0.001 <0.001 -1.05 1.2378 <0.001 <0.001 Amino acids S-lactoylglutathione HMDB0001066 C03451 0.1827 0.26736 0.039 0.5327 0.011 0.0254 -0.24 1.068 <0.001 <0.001 0.15 1.1857 <0.001 <0.001 Amino acids L-asparagine HMDB0000168 C00152 0.170 0.258 0.14 0.7073 <0.001 <0.001 0.36 1.311 <0.001 <0.001 0.46 1.4447 <0.001 <0.001 Amino acids 5-aminovaleric acid HMDB0003355 C00431 0.5277 0.63326 0.071 0.2779 0.406 0.5089 0.251 0.675 <0.001 0.002 0.52 1.107 0.01 0.0083 Amino acids L-glutamine HMDB0000641 C00064 0.006 0.018 -0.51 1.129 <0.001 0.001 -0.78 1.45 <0.001 <0.001 0.53 1.2554 <0.001 <0.001 Amino acids L-kynurenine HMDB0000684 C00328 0.1056 0.1811 0.033 0.5986 0.004 0.0106 0.895 1.352 <0.001 <0.001 0.56 1.1805 <0.001 <0.001 Amino acids L-phenylalanine HMDB0000159 C00079 <0.001 <0.001 0.76 2.0032 <0.001 <0.001 0.76 1.745 <0.001 <0.001 0.60 1.6617 <0.001 <0.001 Amino acids Hexanoylglycine HMDB0000701 - 0.9843 0.98427 -0.11 0.1943 0.216 0.3029 -0.2 0.48 <0.001 <0.001 0.65 1.4672 <0.001 <0.001 Amino acids L-isoleucine HMDB0000172 C00407 0.465 0.571 0.13 0.2977 0.2945 0.383 0.09 0.757 <0.001 <0.001 0.70 1.2506 0.001 0.0016 Amino acids L-tyrosine HMDB0000158 C00082 0.1348 0.21643 0.297 0.5804 0.302 0.3899 0.264 0.588 <0.001 <0.001 0.71 1.112 0.00 0.0063 Amino acids L-norleucine HMDB0001645 C01933 0.522 0.629 -0.10 0.2963 0.7689 0.835 -0.07 0.554 <0.001 0.002 0.75 1.1324 <0.001 0.0016 Amino acids Beta-alanine HMDB0000056 C00099 0.6217 0.70196 0.075 0.2938 0.910 0.9521 -0.03 0.03 <0.001 <0.001 0.76 1.1334 <0.001 <0.001 Amino acids L-proline HMDB0000162 C00148 0.115 0.192 -0.21 0.6577 0.8938 0.942 0.05 0.152 <0.001 <0.001 0.80 1.3218 <0.001 <0.001 Amino acids Dl-serine HMDB0000187 C00716 0.7908 0.82013 0.029 0.1422 0.650 0.744 -0.21 0.346 <0.001 <0.001 0.87 1.6342 <0.001 <0.001 Amino acids D-aspartate HMDB0006483 C00402 <0.001 <0.001 1.46 1.936 <0.001 0.002 1.24 1.57 <0.001 <0.001 1.30 1.5896 <0.001 <0.001 Amino acids L-histidine HMDB0000177 C00135 0.7374 0.77753 0.128 0.2918 <0.001 <0.001 -0.93 1.636 <0.001 <0.001 1.36 1.6858 <0.001 <0.001 Amino acids L-glutamic acid HMDB0000148 C00025 <0.001 <0.001 0.74 1.7166 <0.001 <0.001 0.90 1.579 <0.001 <0.001 1.44 1.7968 <0.001 <0.001 Amino acids L-lysine HMDB0000182 C00047 0.2107 0.29826 0.622 0.6883 0.650 0.744 0.274 0.566 <0.001 <0.001 2.15 1.7559 <0.001 <0.001 Amino acids N-acetylmethionine HMDB0011745 C02712 0.258 0.352 0.25 0.5278 <0.001 <0.001 2.46 1.869 <0.001 <0.001 2.36 1.2883 <0.001 <0.001 Amino acids D-ornithine HMDB0003374 C00515 0.1827 0.26736 0.563 0.8691 0.005 0.0122 0.911 1.442 <0.001 <0.001 3.47 1.6865 <0.001 <0.001 Amino acids N-acetylornithine HMDB0003357 C00437 <0.001 <0.001 4.60 1.7166 <0.001 <0.001 4.01 1.631 <0.001 <0.001 5.04 1.3389 <0.001 <0.001 Amino acids 3-methoxytyrosine HMDB0001434 - 0.5145 0.62333 -0.12 0.2264 0.087 0.1429 -0.38 0.583 0.036 0.058 -0.53 0.1469 0.16 0.1754 Amino acids Betaine HMDB0000043 C00719 0.038 0.078 0.47 0.9209 0.1053 0.168 -0.34 0.784 0.0413 0.065 0.32 0.7014 <0.001 0.0015 Amino acids Creatine HMDB0000064 C00300 0.6629 0.72636 0.052 0.1356 0.152 0.2238 0.256 0.901 0.0522 0.080 0.18 0.6083 0.12 0.1378 Amino acids L-threonine HMDB0000167 C00188 0.002 0.007 -0.58 1.2475 <0.001 <0.001 -1.08 1.713 0.0677 0.102 0.23 0.6784 <0.001 <0.001 Amino acids N-acetyl-d-tryptophan HMDB0013713 - <0.001 <0.001 1.796 2.0075 <0.001 <0.001 1.642 0.862 0.1098 0.157 0.23 0.5085 <0.001 <0.001 Amino acids L-threonic acid HMDB0062620 C01620 0.011 0.027 -0.91 1.1489 0.0523 0.093 -0.82 0.721 0.1902 0.263 -0.25 0.4405 0.0414 0.0519 Amino acids Cinnamoylglycine HMDB0011621 - 0.0379 0.07764 -2.32 0.334 0.005 0.0138 -2.78 0.947 0.2497 0.331 -1.08 0.4048 0.02 0.021 Amino acids 1-methylhistidine HMDB0000479 C01152 0.097 0.169 0.42 0.5338 0.2471 0.331 0.87 0.757 0.2497 0.331 0.61 0.4111 0.3989 0.4103 Amino acids Capryloylglycine HMDB0000832 - 0.0032 0.01018 0.668 0.383 0.087 0.1429 -0.18 0.775 0.2653 0.346 0.13 0.0884 <0.001 <0.001 Amino acids Tyrosylalanine HMDB0029098 - 0.006 0.017 -2.11 1.1888 0.4371 0.537 1.17 0.073 0.2815 0.362 0.87 0.0972 <0.001 <0.001 Amino acids Valylproline HMDB0029135 - 0.8792 0.89701 -0.02 0.1011 0.087 0.1429 0.424 0.757 0.3719 0.459 0.08 0.3003 0.22 0.2352 Amino acids L-valine HMDB0000883 C00183 0.540 0.639 -0.32 0.1266 0.2471 0.331 0.26 0.688 0.4022 0.487 -0.13 0.3295 0.1933 0.2081 Amino acids L-tryptophan HMDB0000929 C00078 0.0026 0.00898 -0.4 1.2159 0.004 0.0104 -0.57 1.181 0.4248 0.510 0.09 0.3291 <0.001 <0.001 Amino acids N-acetylvaline HMDB0011757 - <0.001 <0.001 1.68 2.2194 <0.001 0.001 0.46 1.314 0.4337 0.518 -0.06 0.2726 <0.001 <0.001 Amino acids Pyroglutamate HMDB0000267 C01879 0.0032 0.01018 1.206 1.4344 0.002 0.006 0.402 1.317 0.5009 0.576 0.01 0.4296 0.00 0.0023 Amino acids Dl-2-aminocaprylic acid HMDB0000991 - 0.046 0.091 -0.76 0.2538 0.0597 0.104 -1.17 0.458 0.5009 0.576 -0.18 0.0414 0.0632 0.0766 Amino acids Glycyl-l-leucine HMDB0000759 C02155 0.2107 0.29826 -0.67 0.0197 0.186 0.2679 -0.41 0.348 0.573 0.650 -0.35 0.1281 0.52 0.529 Amino acids N- HMDB0006344 C04148 0.708 0.756 0.52 0.3379 0.1095 0.171 1.12 0.693 0.5981 0.667 -0.63 0.1994 0.1812 0.196 Amino acids L-arginine HMDB0000517 C00062 0.5827 0.67983 -0.07 0.2749 <0.001 0.0015 -0.78 1.341 0.6093 0.676 -0.07 0.1231 <0.001 <0.001 Amino acids N-methyl-l-glutamate HMDB0062660 C01046 0.022 0.051 0.34 0.7411 0.0135 0.029 0.43 1.185 0.7029 0.757 0.12 0.2237 0.0083 0.0117 Benzenoids 3-hydroxybenzoate HMDB0002466 C00587 0.3318 0.43551 4.07 1.1504 1.000 1 5.667 1.33 0.0037 0.007 -0.36 0.0483 0.10 0.1132 Benzenoids Homogentisate HMDB0000130 C00544 0.146 0.227 -0.44 0.6064 0.9362 0.958 0.36 0.583 0.0029 0.006 3.37 0.1422 <0.001 <0.001 Benzenoids 4-hydroxybenzoate HMDB0000500 C00156 <0.001 <0.001 -0.58 0.3252 0.001 0.0041 -0.44 0.411 <0.001 0.002 -0.39 0.2614 <0.001 <0.001 3,4-dihydroxyphenyl Benzenoids glycol HMDB0000318 C05576 0.075 0.138 -0.17 0.5729 0.2254 0.307 -0.24 0.211 0.0055 0.010 -0.10 0.4837 0.1069 0.1214 Benzenoids 4-ethylphenol HMDB0029306 C13637 0.0379 0.07764 -0.53 0.2892 0.030 0.0561 -0.46 0.463 <0.001 <0.001 -0.54 0.5119 0.01 0.0121 Benzenoids 4-methylcatechol HMDB0000873 C06730 0.115 0.192 -1.53 0.1384 <0.001 <0.001 -3.94 1.167 <0.001 0.002 -2.94 0.5902 <0.001 0.0012 Benzenoids Anthranilic acid HMDB0001123 C00108 <0.001 <0.001 0.926 1.6657 <0.001 <0.001 0.983 1.209 0.0243 0.040 0.14 0.6255 <0.001 <0.001 Benzenoids Dihydroxymandelic acid HMDB0001866 C05580 0.275 0.369 -0.62 0.2896 0.0066 0.016 -2.50 0.921 0.0029 0.006 -1.73 0.6349 0.0067 0.0095 Benzenoids Mandelate HMDB0000703 C01984 0.1056 0.1811 -0.38 0.2688 0.769 0.8352 -0.02 0.287 <0.001 <0.001 -1.90 0.9602 <0.001 <0.001 Benzenoids Monobutyl phthalate HMDB0013247 - <0.001 0.003 -1.55 0.2536 <0.001 <0.001 -2.10 0.973 <0.001 <0.001 -2.57 0.9983 <0.001 <0.001 4-hydroxyphenylpyruvic Benzenoids acid HMDB0000707 C01179 <0.001 <0.001 -1.76 1.8922 0.001 0.0039 -1.05 1.444 <0.001 <0.001 -6.71 1.831 <0.001 <0.001 Mono(2-ethylhexyl) Benzenoids phthalate (mehp) HMDB0013248 C03343 <0.001 <0.001 -2.55 2.0726 0.022 0.045 -2.04 0.417 <0.001 <0.001 -2.96 1.692 <0.001 <0.001 Benzenoids 2-methylhippuric acid HMDB0011723 - <0.001 <0.001 2.048 1.4231 <0.001 <0.001 1.176 1.737 <0.001 <0.001 -2.36 1.4519 <0.001 <0.001 Benzenoids Isohomovanillic acid HMDB0000333 - <0.001 <0.001 -1.73 0.4035 <0.001 <0.001 -1.92 1.789 <0.001 <0.001 -2.19 1.6784 <0.001 <0.001 3-hydroxyanthranilic Benzenoids acid HMDB0001476 C00632 <0.001 <0.001 -1.43 0.0512 <0.001 <0.001 -1.4 1.772 <0.001 <0.001 -1.62 1.677 <0.001 <0.001 Benzenoids 4-hydroxybenzaldehyde HMDB0011718 C00633 <0.001 <0.001 -0.63 1.7356 0.5743 0.676 -0.13 0.07 <0.001 <0.001 -1.54 1.8088 <0.001 <0.001 Benzenoids Epinephrine HMDB0000068 C00788 0.0122 0.03051 0.656 1.0316 0.852 0.9095 -0.04 0.64 <0.001 <0.001 -1.31 1.6769 <0.001 <0.001 Benzenoids Dl-metanephrine HMDB0062493 C05588 0.002 0.008 1.20 1.0865 0.0768 0.131 0.38 0.972 <0.001 <0.001 -1.27 1.458 <0.001 <0.001 Benzenoids Phenyl acetate HMDB0040733 C00548 0.0056 0.01663 -0.34 0.2274 0.001 0.0041 -0.47 1.352 <0.001 0.002 -0.36 1.144 0.00 0.0031 Benzenoids 4-aminobenzoic acid HMDB0001392 C00568 <0.001 0.001 0.86 0.9169 0.1105 0.172 0.16 0.771 <0.001 <0.001 0.38 1.2497 <0.001 <0.001 Benzenoids 4'-hydroxydiclofenac HMDB0013974 - 0.5941 0.68671 0.037 0.3495 0.168 0.2452 0.176 0.635 0.0327 0.053 0.13 0.7607 0.16 0.174 Benzenoids 2-hydroxyhippuric acid HMDB0000840 C07588 0.018 0.042 -1.32 0.3275 0.7283 0.819 -0.03 0.481 0.1474 0.209 0.51 0.2863 0.0134 0.018 2-quinolinecarboxylic Benzenoids acid HMDB0000842 C06325 0.0758 0.13946 -0.49 0.8929 0.035 0.063 0.727 0.652 0.1998 0.275 0.33 0.3889 0.00 0.0031 2,4-dihydroxybenzoic Benzenoids acid HMDB0029666 - <0.001 <0.001 -1.51 1.5378 0.1095 0.171 -1.71 0.693 0.2815 0.362 0.27 0.5249 <0.001 <0.001 Benzenoids Monomethyl phthalate HMDB0002130 - 0.6045 0.69555 -0.04 0.2424 0.470 0.5717 0.123 0.678 0.2815 0.362 0.07 0.4408 0.33 0.3405 Benzenoids Hippurate HMDB0000714 C01586 0.025 0.055 -2.06 0.6406 0.7689 0.835 -0.06 0.349 0.3157 0.402 -0.55 0.2615 0.0855 0.1004 Benzenoids Phenol HMDB0013674 C00146 0.0307 0.06731 -0.74 0.1758 0.008 0.0192 -1.6 0.041 0.3919 0.477 -0.35 0.1255 0.01 0.0155 Benzenoids 4-toluic acid HMDB0029635 C01454 0.046 0.091 0.38 0.4689 0.1519 0.224 0.50 0.566 0.5009 0.576 0.03 0.0434 0.065 0.078 Benzenoids 4-methylphenol HMDB0001858 C01468 0.7374 0.77753 0.679 0.5414 0.347 0.44 -1.26 0.427 0.8989 0.917 0.12 0.3156 0.85 0.8603 Bile acids Taurocholic acid HMDB0000036 C05122 0.038 0.078 1.00 0.0116 0.0016 0.005 2.79 0.784 0.0297 0.048 0.51 0.0192 0.0018 0.0028 Bile acids Deoxycholic acid HMDB0000626 C04483 0.2416 0.33448 0.41 0.6297 0.205 0.2888 -0.63 0.668 <0.001 <0.001 0.95 1.0923 <0.001 <0.001 Bile acids Glycocholic acid HMDB0000331 C01921 0.798 0.820 0.35 0.0392 0.0257 0.051 2.00 0.614 0.2497 0.331 -0.23 0.2416 0.0132 0.0178 Glycoursodeoxycholic Bile acids acid HMDB0000708 - 0.1697 0.25761 0.781 0.5725 0.019 0.0388 2.16 1.044 0.3338 0.421 0.88 0.4162 0.06 0.0772 Bile acids Cholate HMDB0000619 C00695 0.373 0.477 -0.03 0.7301 0.5382 0.643 0.13 0.442 0.5981 0.667 0.08 0.343 0.2895 0.304 Bile acids Glycocholate HMDB0000138 C01921 0.6217 0.70196 0.231 0.1298 0.011 0.0254 2.247 0.69 0.6237 0.683 0.07 0.2939 0.02 0.0206 Taurolithocholic acid 3- Bile acids sulfate HMDB0002580 C03642 0.226 0.314 0.99 0.552 0.9362 0.958 -0.34 0.13 0.6237 0.683 -1.36 0.0171 0.3032 0.317 Taurochenodeoxycholic Bile acids acid HMDB0000951 C05465 0.1458 0.22681 1.202 0.478 <0.001 0.0028 2.331 1.225 0.73 0.776 -0.45 0.1752 <0.001 0.0013
Bile acids Glycochenodeoxycholat HMDB0000637 C05466 0.226 0.314 0.43 0.6022 0.0298 0.056 0.94 1.021 0.8989 0.917 -0.21 0.35 0.1312 0.1469 Biotin Biotin HMDB0000030 C00120 0.128 0.20815 -0.1 0.6879 0.936 0.9584 -0.01 0.706 <0.001 <0.001 0.35 1.3106 <0.001 <0.001 Carbohydrates Alpha-d-glucose HMDB0003345 C00267 0.010 0.024 0.67 0.9927 <0.001 0.003 -0.54 1.069 0.0219 0.037 -0.18 0.4208 <0.001 <0.001 Carbohydrates D-lyxose HMDB0003402 C00476 <0.001 <0.001 0.822 1.4656 0.005 0.0138 -0.48 1.21 0.0049 0.009 -0.29 0.7102 <0.001 <0.001 Carbohydrates Muramic acid HMDB0003254 - 0.708 0.756 0.12 0.1443 0.0257 0.051 -0.74 0.809 <0.001 <0.001 -5.13 1.8269 <0.001 <0.001 Carbohydrates N-acetylneuraminic acid HMDB0000773 C19909 <0.001 <0.001 1.963 1.113 <0.001 <0.001 2.308 1.694 <0.001 <0.001 -4.34 1.7562 <0.001 <0.001 Carbohydrates D-glucosamine HMDB0030091 C08349 0.737 0.778 0.08 0.3633 0.8517 0.909 0.03 0.05 <0.001 <0.001 -2.64 1.8273 <0.001 <0.001 Carbohydrates N-acetylneuraminate HMDB0000230 C00270 0.0564 0.10932 0.545 0.9743 0.002 0.006 0.893 0.963 <0.001 <0.001 -2.21 1.4997 <0.001 <0.001 Carbohydrates Gluconic acid HMDB0000625 C00257 <0.001 <0.001 0.49 1.2811 <0.001 <0.001 1.61 0.825 <0.001 <0.001 2.01 1.4428 <0.001 <0.001 Cinnamic acids Caffeic acid HMDB0001964 C01197 0.0816 0.14785 -1.02 0.9003 0.137 0.2049 -1.03 0.853 0.0396 0.063 -0.83 0.9795 0.18 0.1918 Cinnamic acids Sinapinic acid HMDB0032616 C00482 0.417 0.518 0.04 0.3123 0.0523 0.093 1.22 0.7 0.5244 0.598 0.02 0.3008 0.0555 0.0682 Cinnamic acids Trans-cinnamate HMDB0000930 C00423 <0.001 <0.001 2.163 1.5915 <0.001 0.0022 -1.54 0.059 <0.001 <0.001 -1.68 1.6046 <0.001 <0.001 Fatty acids Lauric acid HMDB0000638 C02679 0.183 0.267 -0.24 0.5214 <0.001 <0.001 -0.89 1.486 0.0177 0.030 -0.71 0.1695 <0.001 <0.001 Fatty acids Glutarylcarnitine HMDB0013130 - <0.001 <0.001 2.293 1.5109 0.008 0.0192 1.095 1.122 <0.001 <0.001 -2.48 0.3866 <0.001 <0.001 Fatty acids Gamma-linolenic acid HMDB0003073 C06426 0.567 0.665 0.06 0.4361 <0.001 0.001 0.85 1.218 0.0243 0.040 0.43 0.5789 0.0011 0.0017 Fatty acids Caprylic acid HMDB0000482 C06423 0.0084 0.02288 -0.31 1.0097 0.769 0.8352 2.495 0.848 0.0127 0.022 0.32 0.6574 <0.001 <0.001 Fatty acids Ethyl myristate HMDB0034153 - 0.147 0.227 0.24 0.6608 0.144 0.215 -0.32 0.689 0.0297 0.048 -0.57 0.7535 0.0047 0.0067 Fatty acids Sulcatol HMDB0030030 C07288 0.0971 0.1687 0.063 0.697 <0.001 <0.001 1.381 0.807 0.0055 0.010 0.34 0.8195 <0.001 <0.001 Fatty acids Dodecanedioic acid HMDB0000623 C02678 <0.001 <0.001 -2.08 1.8519 <0.001 <0.001 -1.73 1.528 <0.001 <0.001 -2.01 1.0868 <0.001 <0.001 Fatty acids Dethiobiotin HMDB0003581 C01909 <0.001 <0.001 -2.24 1.898 <0.001 <0.001 1.1 1.281 <0.001 <0.001 -1.54 1.3269 <0.001 <0.001 Fatty acids 3-hydroxydecanoic acid HMDB0002203 - <0.001 <0.001 -0.76 1.4184 0.0298 0.056 -0.34 1.057 <0.001 <0.001 -1.34 1.0914 <0.001 <0.001 16- Fatty acids hydroxyhexadecanoic HMDB0006294 C18218 0.0095 0.02444 0.47 1.0618 0.574 0.6763 -0.25 0.508 <0.001 <0.001 -1.03 1.6345 <0.001 <0.001 Fatty acids Arachidonic acid HMDB0001043 C00219 0.344 0.449 0.14 0.4782 0.131 0.200 -0.25 0.631 <0.001 <0.001 -0.69 1.2291 <0.001 <0.001 Fatty acids Isobutyric acid HMDB0001873 C02632 0.0197 0.04598 0.176 0.8373 0.023 0.0463 -0.17 1.011 <0.001 <0.001 0.20 1.1638 <0.001 <0.001 Fatty acids Adipate HMDB0000448 C06104 <0.001 <0.001 0.97 0.8606 <0.001 <0.001 1.75 1.27 <0.001 <0.001 0.34 1.4453 <0.001 <0.001 Fatty acids 6-carboxyhexanoate HMDB0000857 C02656 <0.001 <0.001 0.827 1.6822 <0.001 <0.001 2.908 1.251 <0.001 <0.001 0.41 1.3402 <0.001 <0.001 Fatty acids Hexadecanamide HMDB0012273 - <0.001 <0.001 1.26 1.7976 0.0257 0.051 0.34 1.062 <0.001 <0.001 0.62 1.1851 <0.001 <0.001 Fatty acids Sebacic acid HMDB0000792 C08277 <0.001 <0.001 1.671 1.7722 <0.001 <0.001 3.5 0.628 <0.001 <0.001 2.27 1.2847 <0.001 <0.001 Fatty acids Oleamide HMDB0002117 C19670 <0.001 <0.001 2.33 1.6724 0.0976 0.158 -0.58 0.046 <0.001 0.002 2.31 1.2424 <0.001 <0.001 Fatty acids Palmitoylcarnitine HMDB0000222 C02990 0.3732 0.47744 0.321 0.3425 0.005 0.0122 0.937 1.21 <0.001 <0.001 2.62 1.6591 <0.001 <0.001 Fatty acids Hexanoylcarnitine HMDB0000705 - 0.679 0.740 0.29 0.3606 0.0345 0.063 1.71 0.89 <0.001 <0.001 2.78 1.2845 <0.001 <0.001 Fatty acids Azelaic acid HMDB0000784 C08261 <0.001 <0.001 3.717 1.5742 <0.001 <0.001 6.575 1.122 <0.001 <0.001 2.80 1.7577 <0.001 <0.001 Fatty acids Propionylcarnitine HMDB0000824 C03017 0.001 0.005 1.35 0.6504 <0.001 0.002 2.53 1.289 <0.001 <0.001 6.67 1.5714 <0.001 <0.001 Fatty acids O-acetylcarnitine HMDB0000201 C02571 0.0095 0.02444 0.5 0.5734 0.137 0.2049 0.328 0.833 <0.001 <0.001 10.15 1.3234 <0.001 <0.001 Fatty acids Oleate HMDB0000207 C00712 0.016 0.040 0.45 1.0761 0.5033 0.604 0.23 0.487 0.0531 0.081 0.35 0.654 0.0911 0.1057 Fatty acids Lauroylcarnitine HMDB0002250 - 0.1963 0.28269 -0.15 0.8379 0.503 0.604 -0.21 0.503 0.0737 0.109 1.01 0.5453 <0.001 0.001 8z,11z,14z- Fatty acids eicosatrienoic acid HMDB0002925 C03242 0.002 0.007 0.58 1.2425 0.0045 0.012 0.45 1.198 0.0868 0.127 0.41 0.5451 0.0136 0.0182 Fatty acids Linoleic acid HMDB0000673 C01595 0.1835 0.26736 0.3 0.6703 0.769 0.8352 -0.12 0.023 0.1001 0.145 -0.43 0.5959 0.01 0.0169 Fatty acids Decanoic acid HMDB0000511 C01571 0.008 0.023 -0.34 1.1473 0.4371 0.537 2.57 0.874 0.1098 0.157 -0.22 0.1429 0.07 0.0832 Fatty acids L-carnitine HMDB0000062 C00318 <0.001 0.00254 0.822 1.3897 <0.001 0.0012 2.076 1.311 0.1275 0.182 0.06 0.5486 <0.001 <0.001 Fatty acids 3-hydroxybutanoate HMDB0000011 C01089 0.275 0.369 0.11 0.7747 0.2254 0.307 -0.53 0.315 0.1813 0.252 -0.24 0.1169 0.0406 0.0512 Fatty acids Dl-carnitine HMDB0002095 - 0.2107 0.29826 0.054 0.4612 0.728 0.8194 0.033 0.065 0.2205 0.300 -0.18 0.384 0.18 0.196 9-oxo-10(e),12(e)- Fatty acids octadecadienoic acid HMDB0004669 C14766 0.312 0.416 0.33 0.2066 0.0345 0.063 0.88 0.791 0.3157 0.402 0.38 0.2903 0.148 0.1643 4-hydroxybutyric acid Fatty acids (ghb) HMDB0000710 C00989 <0.001 <0.001 1.431 1.5597 0.347 0.44 0.341 0.665 0.3526 0.438 0.30 0.4016 <0.001 <0.001 Cis-5,8,11,14,17- Fatty acids eicosapentaenoic acid HMDB0001999 C06428 0.146 0.227 0.30 0.5911 0.8938 0.942 -0.15 0.361 0.3526 0.438 -0.04 0.4888 0.4554 0.4665 Fatty acids Decanoylcarnitine HMDB0000651 - 0.0681 0.12878 -0.85 0.8955 0.979 0.9865 0.008 0.16 0.3526 0.438 1.17 0.3485 0.01 0.0107
3-hydroxy-3- Fatty acids methylbutanoic acid HMDB0000754 C20827 0.183 0.267 0.15 0.8034 0.2701 0.356 -0.58 0.293 0.5244 0.598 -0.14 0.0665 0.0856 0.1004 Fatty acids Palmitoleic acid HMDB0003229 C08362 0.9533 0.96482 0.015 0.1129 0.755 0.8352 -0.11 0.154 0.675 0.730 0.10 0.1503 0.90 0.9062 Fatty acids Hexadecanedioic acid HMDB0000672 C19615 0.708 0.756 0.04 0.4163 0.2701 0.356 0.15 0.563 0.7575 0.802 -0.35 0.1767 0.5165 0.527 Fatty acids Suberic acid HMDB0000893 C08278 0.0379 0.07764 0.514 0.9295 <0.001 <0.001 1.645 0.896 0.7853 0.828 -0.06 0.1647 <0.001 <0.001 Fatty acids Methyl jasmonate HMDB0036583 C11512 0.125 0.204 0.42 0.7495 0.0016 0.005 -1.32 1.322 0.8134 0.851 -0.10 0.2372 <0.001 <0.001 Fatty acids Tetradecanedioic acid HMDB0000872 - 0.9215 0.93635 0.305 0.4043 0.769 0.8352 0.102 0.168 0.9566 0.960 0.35 0.3924 0.99 0.9947 Hydroxycinnamic acids 2-hydroxycinnamic acid HMDB0002641 C01772 0.115 0.192 0.32 0.5918 0.2466 0.331 0.28 0.64 <0.001 <0.001 0.72 1.2773 0.0012 0.0019 Imidazoles Imidazoleacetic acid HMDB0002024 C02835 <0.001 <0.001 0.903 1.0188 0.002 0.005 0.412 1.343 0.0025 0.005 0.30 0.8189 <0.001 <0.001 Imidazoles Urocanic acid HMDB0000301 C00785 0.594 0.687 0.06 0.5268 0.2945 0.383 -0.23 0.378 <0.001 <0.001 0.92 1.0296 <0.001 <0.001 Methylimidazoleacetic Imidazoles acid HMDB0002820 C05828 0.4175 0.51822 0.093 0.0161 0.003 0.0088 1.09 0.919 0.0435 0.068 0.25 0.2705 0.00 0.0049 Indoles Indole-3-methyl acetate HMDB0029738 C20635 0.489 0.596 0.80 0.3416 0.4696 0.572 -0.36 0.558 0.0197 0.033 2.46 0.7348 0.0389 0.0493 Indoles Indole-3-butyric acid HMDB0002096 C11284 0.0036 0.0115 1.01 1.1482 0.002 0.0074 2.241 1.195 <0.001 <0.001 2.03 0.7928 <0.001 <0.001 Indoles L-5-hydroxytryptophan HMDB0000472 C01017 <0.001 0.003 0.78 1.208 <0.001 0.003 1.42 1.328 <0.001 <0.001 0.87 0.9032 <0.001 <0.001 Indoles Indole-3-acetamide HMDB0029739 C02693 <0.001 <0.001 -2.26 2.1848 0.085 0.1429 -0.38 0.729 <0.001 <0.001 -5.69 1.8601 <0.001 <0.001 Indoles 5-hydroxyindoleacetate HMDB0000763 C05635 0.007 0.020 0.47 0.9899 <0.001 0.002 1.23 1.4 <0.001 <0.001 0.75 1.0693 <0.001 <0.001 Indoles Indole-3-acetaldehyde HMDB0001190 C00637 0.0056 0.01663 0.411 1.0309 <0.001 <0.001 1.744 1.378 <0.001 <0.001 0.88 1.328 <0.001 <0.001 Indoles N-acetylserotonin HMDB0001238 C00978 0.003 0.009 -0.26 1.3275 <0.001 <0.001 -0.49 1.547 <0.001 <0.001 3.07 1.0759 <0.001 <0.001 Indoles Indole-3-pyruvic acid HMDB0060484 C00331 0.0014 0.00536 -1.35 0.5906 <0.001 <0.001 -1.64 1.27 <0.001 <0.001 5.66 1.3306 <0.001 <0.001 Indoles Indole HMDB0000738 C00463 0.017 0.041 -0.26 1.0189 0.1225 0.189 -0.32 0.86 0.057 0.086 0.16 0.5501 <0.001 0.0011 Indoles Indole-3-lactic acid HMDB0000671 C02043 0.0415 0.08365 -0.32 0.927 0.002 0.0074 1.06 1.147 0.2653 0.346 0.17 0.4671 <0.001 <0.001 Indoles Indole-3-acetic acid HMDB0000197 C00954 <0.001 0.002 -0.60 1.2667 0.5743 0.676 0.12 0.267 0.8702 0.899 0.10 0.2476 0.0018 0.0027 Indoles 2-oxindole HMDB0061918 C12312 0.3291 0.43422 -0.28 0.4543 0.503 0.604 -0.58 0.385 0.9277 0.939 -0.06 0.1884 0.64 0.6524 Lipids Testosterone HMDB0003193 C11134 <0.001 0.003 5.18 1.2285 0.0016 0.005 6.52 1.323 <0.001 <0.001 -0.40 0.2127 <0.001 <0.001 Lipids Desoxycortone HMDB0000016 C03205 <0.001 <0.001 1.461 1.6687 <0.001 <0.001 1.497 1.736 <0.001 <0.001 0.94 0.7677 <0.001 <0.001 Lipids Perillic acid HMDB0004586 C11924 0.441 0.544 0.29 0.2569 0.3475 0.440 -0.41 0.539 0.0127 0.022 -0.72 0.8404 0.0049 0.007 Lipids Testosterone sulfate HMDB0002833 - 0.6507 0.71609 -0.14 0.1226 <0.001 0.0022 -1.09 1.489 0.0093 0.017 -0.77 0.8735 0.01 0.0121 Lipids Coenzyme q2 HMDB0006709 C00399 0.021 0.048 0.56 0.9541 <0.001 <0.001 1.75 1.262 <0.001 <0.001 -1.74 0.9403 <0.001 <0.001 Lipids 1-oleoyl-rac-glycerol HMDB0011567 - <0.001 <0.001 4.417 1.7869 <0.001 <0.001 5.912 0.905 <0.001 <0.001 4.47 0.9459 <0.001 <0.001 Lipids Palmitoyl sphingomyelin HMDB0061712 - <0.001 <0.001 0.97 1.6054 0.1683 0.245 0.11 0.672 <0.001 <0.001 0.52 1.1082 <0.001 <0.001 Lipids Alpha-tocopherol HMDB0001893 C02477 0.0052 0.01604 0.544 1.2201 0.295 0.3826 0.358 0.636 <0.001 <0.001 0.58 1.156 0.01 0.0184 D-erythro-sphingosine 1- Lipids phosphate HMDB0000277 C06124 <0.001 0.001 -0.45 1.3921 0.1861 0.268 0.18 0.787 <0.001 <0.001 0.61 1.3743 <0.001 <0.001 Lipids Tetrahydrocortisone HMDB0000903 C05470 0.0816 0.14785 0.563 0.9128 0.010 0.0233 0.55 1.119 <0.001 <0.001 1.36 1.275 <0.001 <0.001 Lipids Cortisol HMDB0000063 C00735 <0.001 <0.001 1.23 1.5382 <0.001 <0.001 1.07 1.742 <0.001 <0.001 1.66 1.532 <0.001 <0.001 Lipids Cortisone HMDB0002802 C00762 <0.001 <0.001 0.938 1.4806 0.376 0.4738 0.254 0.563 <0.001 <0.001 1.99 1.6781 <0.001 <0.001 Lipids Epitestosterone HMDB0000628 - 0.006 0.017 1.07 1.0573 <0.001 <0.001 3.11 0.82 <0.001 <0.001 2.01 1.3094 <0.001 <0.001 Lipids Medroxyprogesterone HMDB0001939 C07119 0.089 0.15803 -0.85 0.2758 <0.001 <0.001 4.322 1.933 <0.001 <0.001 4.80 1.2956 <0.001 <0.001 5-alpha-pregnan-3,20- Lipids dione HMDB0003759 C03681 0.352 0.455 0.20 0.5995 0.7689 0.835 0.11 0.478 0.0522 0.080 -1.43 0.3839 0.063 0.0766 Androsterone Lipids glucuronide HMDB0002829 C11135 0.001 0.00396 -0.94 1.422 0.137 0.2049 0.715 0.725 0.3823 0.470 -0.21 0.3158 <0.001 0.001 Lipids 19-nortestosterone HMDB0002725 C07254 0.650 0.716 0.40 0.147 0.0298 0.056 1.46 0.509 0.4555 0.534 0.45 0.0124 0.0345 0.0439 Lipids Progesterone HMDB0001830 C00410 0.0383 0.07778 0.58 0.8772 0.225 0.307 -0.64 0.222 0.5981 0.667 -0.25 0.0893 0.03 0.037 Lipids Coenzyme q1 HMDB0002012 - 0.622 0.702 0.15 0.4405 0.9787 0.987 -0.13 0.749 0.6237 0.683 -0.22 0.8291 0.3427 0.354 2,6-di-tert-butyl-1,4- Lipids benzoquinone HMDB0013817 - 0.1245 0.20373 -0.4 0.3541 0.016 0.0341 -0.54 0.874 0.73 0.776 0.36 0.2441 0.03 0.037 Lipids Corticosterone HMDB0001547 C02140 0.708 0.756 -0.03 0.4355 0.003 0.009 0.69 0.784 0.8417 0.873 -0.16 0.2766 0.0461 0.0575 Nucleosides Adenosine HMDB0000050 C00212 <0.001 <0.001 -1.67 0.7191 0.098 0.1577 -0.52 0.549 0.0033 0.006 -1.22 0.5375 <0.001 <0.001
Nucleosides Pseudouridine HMDB0000767 C02067 0.417 0.518 -0.13 0.2493 0.0096 0.023 0.71 1.355 <0.001 <0.001 0.45 0.728 <0.001 <0.001 Nucleosides Xanthosine HMDB0000299 C01762 0.0247 0.05509 0.473 0.8854 <0.001 <0.001 3.638 1.246 <0.001 <0.001 2.36 0.8664 <0.001 <0.001 Nucleosides Angiotensin iv HMDB0001038 C15849 0.125 0.204 -0.98 0.9206 <0.001 <0.001 -1.42 2.064 <0.001 <0.001 -1.86 1.8993 <0.001 <0.001 Nucleosides 5'-methylthioadenosine HMDB0001173 C00170 0.0027 0.00924 -0.63 1.2093 0.005 0.0138 0.743 0.518 <0.001 <0.001 -0.56 1.2378 <0.001 <0.001 Nucleosides Uridine HMDB0000296 C00299 0.146 0.227 -0.52 0.6057 0.9394 0.958 -0.02 0.099 0.0057 0.011 -0.55 1.011 0.0655 0.0782 Nucleosides Inosine HMDB0000195 C00294 <0.001 <0.001 -3.29 1.5318 0.022 0.0447 -3.58 0.263 0.0868 0.127 0.53 0.5281 <0.001 <0.001 Organic acids 4-acetamidobutanoate HMDB0003681 C02946 0.146 0.227 -0.28 0.3438 <0.001 0.001 0.88 1.307 <0.001 <0.001 0.76 0.5725 <0.001 <0.001 Organic acids Acrylic acid HMDB0031647 C00511 <0.001 0.00294 0.672 1.2054 0.032 0.06 -0.46 0.987 0.0159 0.027 -0.56 0.6465 <0.001 <0.001 Organic acids Trans-aconitic acid HMDB0000958 C02341 0.417 0.518 -0.24 0.3072 0.6885 0.782 -0.02 0.668 0.0071 0.013 0.48 0.6884 0.0126 0.017 12-hydroxydodecanoic Organic acids acid HMDB0002059 C08317 0.5404 0.63935 -0.22 0.4397 0.007 0.0162 -1.77 0.952 0.0063 0.011 -1.29 0.8575 0.00 0.002 Organic acids Citrate HMDB0000094 C00158 0.089 0.158 0.24 0.8585 0.9362 0.958 -0.14 0.787 0.009 0.016 0.60 0.8977 0.1329 0.1481 Organic acids Oxoglutaric acid HMDB0000208 C00026 0.089 0.15803 0.27 0.8682 0.936 0.9584 -0.11 0.786 0.0063 0.011 0.62 0.9258 0.11 0.124 Organic acids Pipecolate HMDB0000716 C00408 0.046 0.091 0.46 0.8223 0.218 0.304 -0.30 0.529 0.0022 0.004 0.55 0.9869 0.0014 0.0023 Organic acids Alanyltyrosine HMDB0028699 - 0.1348 0.21643 -0.58 0.1538 0.005 0.0138 -2.44 1.024 <0.001 <0.001 -2.06 1.1496 <0.001 0.0016 Organic acids Acetoacetate HMDB0000060 C00164 0.036 0.077 0.15 0.8947 0.1278 0.196 -0.12 0.718 <0.001 <0.001 0.31 1.2648 <0.001 <0.001 Organic acids 3-ureidopropionic acid HMDB0000026 C02642 0.7674 0.79989 0.004 0.2378 0.611 0.7068 0.104 0.37 <0.001 <0.001 0.76 1.4771 <0.001 <0.001 Organic acids L-(+)-lactic acid HMDB0000190 C00186 0.010 0.024 0.23 0.9414 0.0066 0.016 0.38 1.273 <0.001 <0.001 0.94 1.4703 <0.001 <0.001 Organic acids Taurine HMDB0000251 C00245 0.0901 0.15875 -0.48 0.7193 0.902 0.9475 0.036 0.162 <0.001 <0.001 1.87 1.4882 <0.001 <0.001 Organic acids 3-indoxyl sulphate HMDB0000682 - 0.009 0.024 -0.70 1.211 0.2051 0.289 -0.54 0.24 0.0737 0.109 -0.44 0.4108 0.0794 0.0939 Organic acids Oxalic acid HMDB0002329 C00209 0.6258 0.70196 0.025 0.213 0.005 0.0138 -0.28 1.175 0.1778 0.249 0.07 0.4808 0.00 0.0035 Organic acids 2-oxobutyric acid HMDB0000005 C00109 0.016 0.038 0.48 0.9308 0.0114 0.025 -0.51 0.752 0.233 0.316 -0.17 0.4368 <0.001 <0.001 Organic acids Pyruvic acid HMDB0000243 C00022 0.1827 0.26736 0.262 0.5671 0.101 0.1616 -0.36 0.694 0.5957 0.667 0.08 0.2039 0.03 0.0365 Organic acids Levulinic acid HMDB0000720 - 0.627 0.702 0.09 0.2947 0.0538 0.095 -0.43 0.879 0.6699 0.729 0.07 0.1994 0.0552 0.0682 Organic acids 6-hydroxycaproic acid HMDB0012843 C06103 0.2754 0.36918 -0.12 0.495 0.347 0.44 0.147 0.777 0.6716 0.729 0.03 0.1389 0.23 0.2478 Organonitrogen compounds Choline HMDB0000097 C00114 <0.001 <0.001 0.63 1.8628 <0.001 <0.001 1.02 1.94 <0.001 <0.001 0.79 1.735 <0.001 <0.001 Organonitrogen compounds D-sphingosine HMDB0000252 C00319 <0.001 <0.001 1.846 1.5341 <0.001 <0.001 2.113 1.647 <0.001 <0.001 2.24 1.516 <0.001 <0.001 Organonitrogen compounds Spermidine HMDB0001257 C00315 0.006 0.019 1.36 1.1196 <0.001 <0.001 2.65 1.185 <0.001 <0.001 3.14 1.3326 <0.001 <0.001 Organonitrogen compounds Acetylcholine HMDB0000895 C01996 0.7674 0.79989 0.053 0.287 0.011 0.0254 -0.52 1.035 0.73 0.776 0.03 0.2396 0.03 0.037 Organooxygen compounds Pantothenic acid HMDB0000210 C00864 0.020 0.046 0.52 0.9206 <0.001 <0.001 1.68 1.225 0.0159 0.027 -0.50 0.0008 <0.001 <0.001 Organooxygen compounds Diacetyl HMDB0003407 C00741 0.0084 0.02288 -0.51 0.9885 0.437 0.5373 1.438 1.092 0.0522 0.080 -0.23 0.5616 0.00 0.0054 Others 4-oxoproline - C01877 0.008 0.023 1.14 1.355 0.2051 0.289 -0.18 0.582 0.0063 0.011 -0.46 0.4335 <0.001 <0.001 Others N-oleoyl dopamine - C12272 <0.001 <0.001 -1.81 2.0595 0.005 0.0122 -2.71 0.263 <0.001 <0.001 -2.69 1.9338 <0.001 <0.001 4-hydroxy-l- Others phenylglycine - C12323 <0.001 <0.001 0.93 1.4212 <0.001 <0.001 1.38 1.279 <0.001 <0.001 0.87 1.0854 <0.001 <0.001 11,12-epoxy-(5z,8z,11z)- Others icosatrienoic acid - C14770 <0.001 <0.001 -3.27 1.0576 <0.001 <0.001 2.905 1.659 <0.001 <0.001 2.65 1.2377 <0.001 <0.001 Others 2- HMDB0030524 C14437 <0.001 <0.001 -0.49 1.6841 0.0135 0.029 -0.59 1.39 <0.001 <0.001 3.83 1.2863 <0.001 <0.001 Phenylpropanoic Dl-4-hydroxyphenyllactic acids acid HMDB0000755 C03672 0.9843 0.98427 -0.17 0.0125 0.583 0.6803 0.163 0.323 0.0553 0.084 0.40 0.6595 0.17 0.1885 Phenylpropanoic acids 3-phenyllactic acid HMDB0000748 C05607 0.062 0.118 0.60 0.7215 0.2051 0.289 0.49 0.921 0.3919 0.477 0.22 0.3841 0.2892 0.304 2-amino-1,3,4- Phospholipids octadecanetriol HMDB0004610 C12144 <0.001 <0.001 -2.15 2.1547 <0.001 <0.001 -2.53 2.019 <0.001 <0.001 -2.90 1.8376 <0.001 <0.001 Purines 1-methylxanthine HMDB0010738 C16358 0.859 0.880 -0.39 0.4509 0.0135 0.029 -2.52 0.207 0.0029 0.006 -2.01 0.5731 <0.001 <0.001
Purines 1,3-dimethyluric acid HMDB0001857 - 0.2581 0.35161 -1.58 0.2478 0.077 0.1308 -4.55 0.552 0.0033 0.006 -4.46 0.7327 0.02 0.023 Purines Guanine HMDB0000132 C00242 <0.001 <0.001 -2.37 1.6194 <0.001 0.002 -2.73 0.489 <0.001 <0.001 -2.11 1.235 <0.001 <0.001 Purines Adenine HMDB0000034 C00147 0.0147 0.03644 -0.27 1.0969 0.098 0.1577 -0.38 0.509 <0.001 <0.001 -1.05 1.6859 <0.001 <0.001 Purines Xanthine HMDB0000292 C00385 0.069 0.129 0.49 0.7945 0.0273 0.053 0.68 1.134 <0.001 <0.001 1.65 1.5564 <0.001 <0.001 Purines Hypoxanthine HMDB0000157 C00262 0.1963 0.28269 0.35 0.7281 <0.001 <0.001 1.541 1.521 <0.001 <0.001 2.13 1.8049 <0.001 <0.001 Purines 7-methylxanthine HMDB0001991 C16353 0.489 0.596 -1.73 0.0221 0.0768 0.131 -3.72 0.442 0.0435 0.068 -3.04 0.0538 0.0062 0.0089 Purines 7-methylguanine HMDB0000897 C02242 0.9843 0.98427 0.02 0.0777 0.019 0.0388 0.462 0.847 0.2497 0.331 0.24 0.5149 0.10 0.1123 Purines 1-methyluric acid HMDB0003099 C16359 0.258 0.352 -0.17 0.4852 0.2701 0.356 1.07 0.628 0.4555 0.534 -0.26 0.4341 0.1069 0.1214 Purines Uric acid HMDB0000289 C00366 <0.001 0.00125 -0.55 1.4295 <0.001 0.0034 -0.89 1.408 0.8771 0.902 0.02 0.0026 <0.001 <0.001 Pyridines 3-hydroxypicolinic acid HMDB0013188 C18620 <0.001 <0.001 -1.00 0.3146 0.994 0.998 0.00 0.045 <0.001 <0.001 -1.09 1.7924 <0.001 <0.001 Pyridines Pyridoxamine HMDB0001431 C00534 0.5404 0.63935 -0.01 0.2831 0.689 0.7816 0.18 0.186 <0.001 <0.001 1.58 1.3447 <0.001 <0.001 Pyridines Nicotinamide HMDB0001406 C00153 0.038 0.078 0.90 0.9976 <0.001 <0.001 1.96 1.75 <0.001 <0.001 2.48 1.6519 <0.001 <0.001 Pyridines Pyridoxal HMDB0001545 C00250 0.0108 0.0272 0.733 0.5748 0.581 0.6803 -0.1 0.281 0.094 0.137 0.20 0.5012 0.00 0.0047 Pyridines 6-methylnicotinamide HMDB0013704 - 0.322 0.427 -0.13 0.3975 0.4288 0.535 0.08 0.347 0.4555 0.534 0.02 0.295 0.3168 0.3299 Pyridines 4-pyridoxic acid HMDB0000017 C00847 0.5486 0.64607 0.145 0.2229 <0.001 <0.001 2.655 1.208 0.9566 0.960 -0.19 0.3254 <0.001 <0.001 Pyridines Cotinine HMDB0001046 - <0.001 <0.001 -0.52 1.3511 <0.001 <0.001 -1.10 1.66 <0.001 0.002 -0.56 1.1065 <0.001 <0.001 Pyrimidines Dihydrothymine HMDB0000079 C00906 0.0032 0.01018 -0.51 0.7256 0.046 0.0829 -0.45 0.62 <0.001 <0.001 0.66 1.0555 <0.001 <0.001 Pyrimidines Thymine HMDB0000262 C00178 0.004 0.011 -0.40 1.1869 0.0188 0.039 -0.35 1.009 0.2653 0.346 0.19 0.5139 <0.001 <0.001 Pyrrolines Bilirubin HMDB0000054 C00486 0.0095 0.02444 -0.37 0.9187 0.016 0.0341 -0.96 0.71 0.1702 0.240 0.27 0.5101 <0.001 <0.001 Quinolines and derivatives Kynurenic acid HMDB0000715 C01717 0.708 0.756 0.20 0.0612 0.0096 0.023 0.74 1.12 0.8417 0.873 0.09 0.1905 0.0115 0.0158 Tetrahydroisoqui nolines Salsolinol HMDB0042012 C09642 <0.001 <0.001 3.624 2.1251 <0.001 <0.001 4.464 1.977 <0.001 <0.001 2.69 1.742 <0.001 <0.001 Table S3. Metabolites quantified in the discovery cohort by targeted metabolomics (related to figure S3) Cluster Normal VS Mild Normal VS Severe Normal VS Recovery Total Class Name HMDB_ID KEGG_ID number P FDR log2FC VIP P FDR log2FC VIP P FDR log2FC VIP P FDR Amino Acids Lysine HMDB0000 C00047 2 0.9992 1 0 0.1996 0.655 0.7759 0.085 0.213 0.5208 0.8034 0.011 0.51 0.8406 0.862297531 HMDB000 Amino Acids Histidine 0177 C00135 13 0.3844 0.59691 -0.17 0.4865 0.3529 0.498 -0.17 0.585 0.5595 0.813 0.083 0.3946 0.3009 0.396500222 Amino Acids Arginine HMDB0000 C00062 6 0.9143 0.94804 0.016 0.0469 0.0019 0.0113 -0.48 1.643 0.0089 0.0603 -0.37 1.3098 0.0025 0.009752072 Amino Acids Ornithine HMDB000 C00077 4 0.0311 0.18193 0.371 1.5216 <0.001 0.0035 0.981 1.794 <0.001 <0.001 1.557 2.3139 9E-08 <0.001 Amino Acids Glutamine HMDB0000 C00064 8 0.0373 0.18541 -0.36 1.4032 0.0019 0.0113 -0.62 1.791 0.0043 0.0346 -0.48 1.8552 0.0019 0.008166109 Amino Acids Glutamic acid HMDB000 C00025 2 <0.001 0.00256 0.82 1.8495 <0.001 <0.001 1.482 2.015 <0.001 <0.001 1.454 2.6133 3E-07 <0.001 Amino Acids beta-Alanine HMDB0000 C00099 1 0.8807 0.92245 -0.01 0.3399 0.0439 0.1105 0.544 1.32 0.0311 0.157 0.128 0.8346 0.0063 0.020427551 HMDB000 Amino Acids Alanine 0161 C00041 14 0.9472 0.97157 -0.04 0.2593 0.7221 0.8312 -0.06 0.256 0.2497 0.5287 0.17 0.7592 0.7447 0.779998678 Amino Acids Dimethylglycine HMDB0000 C01026 3 0.007 0.077 0.643 1.2967 0.007 0.0273 0.508 1.14 0.1115 0.2883 0.303 0.7737 0.0262 0.061379059 HMDB000 Amino Acids GABA 0112 C00334 5 <0.001 0.01124 -0.59 2.402 0.0188 0.0594 -0.53 1.12 0.0094 0.0603 -0.39 1.6741 0.0018 0.008130636 Amino Acids Serine HMDB0000 C00065 14 0.2662 0.52973 0.168 0.6391 0.6796 0.7982 -0.08 0.224 0.0922 0.2883 0.153 1.0318 0.0932 0.162657087 HMDB000 Amino Acids Threonine 0167 C00188 13 0.0506 0.22879 -0.5 1.3725 0.3944 0.5489 -0.2 0.493 0.6746 0.8462 0.08 0.4134 0.0312 0.06974413 Amino Acids Homoserine HMDB0000 C00263 13 0.0164 0.12118 -0.8 1.5409 0.3513 0.498 -0.19 0.531 0.7181 0.8621 -0.06 0.0236 0.0516 0.109342478 HMDB000 Amino Acids Creatine 0064 C00300 16 0.2917 0.5432 0.341 0.6911 0.0036 0.0165 1.969 1.569 0.2758 0.5435 -0.26 0.5015 0.0002 0.001896725 Carbohydrates Threonic acid HMDB0000 C01620 3 0.5801 0.72152 0.129 0.545 0.2852 0.4368 0.22 0.678 0.4604 0.7545 0.188 0.2305 0.9099 0.914540271 Hydroxypropion HMDB000 Organic Acids ic acid 0700 C01013 12 0.8771 0.92245 -0.13 0.1221 0.0156 0.0509 0.484 0.877 0.4369 0.7322 -0.12 0.5262 0.0089 0.026848137 Amino Acids Homocitrulline HMDB0000 C02427 12 0.3175 0.54459 -0.16 1.1381 0.0036 0.0165 1.153 1.487 0.7739 0.8902 0.164 0.4166 0.0004 0.002455499 Organic Acids Lactic acid HMDB000 C00186 2 0.4647 0.64663 0.105 0.5539 <0.001 <0.001 1.238 2.229 <0.001 <0.001 1.158 2.7261 3E-08 <0.001 Organic Acids Nicotinic acid HMDB0001 C00253 9 0.3352 0.5559 0.002 1.0209 0.9221 0.9607 0 0.48 0.8321 0.9261 0 0.5128 0.5303 0.631915816 HMDB000 Amino Acids Methylcysteine 2108 - 14 0.1546 0.38936 0.392 1.0025 0.347 0.4968 -0.82 0.399 0.1626 0.3763 0.308 0.825 0.1563 0.246843247 Benzoic acids m- HMDB0001 - 11 0.0922 0.29123 -0.13 0.7543 0.8886 0.9357 0.01 0.033 0.8639 0.9384 0.009 0.1152 0.1743 0.26429579 HMDB000 Amino Acids 2-Phenylglycine 2210 - 2 0.0756 0.26378 0.087 0.8204 <0.001 0.003 0.456 1.398 0.0311 0.157 0.083 0.5041 0.0012 0.006010721 Amino Acids Tyrosine HMDB0000 C00082 9 0.5501 0.70505 0.029 0.3511 0.6819 0.7982 0.066 0.302 0.412 0.7067 -0.27 0.3591 0.8629 0.880599077 3,4- Phenylpropanoid Dihydroxyhydro HMDB000 s cinnamic acid 0423 C10447 2 0.3175 0.54459 -0.5 0.2193 <0.001 0.0019 1.653 1.775 <0.001 <0.001 2.003 2.5133 1E-06 <0.001 Amino Acids Asparagine HMDB0000 C00152 4 0.0108 0.09813 -0.34 1.2909 0.8328 0.891 0.075 0.333 0.0094 0.0603 0.199 1.3742 0.0001 0.001460997 Protocatechuic HMDB000 Benzoic acids acid 1856 C00230 9 0.4581 0.64653 -0.05 0.2115 0.4601 0.6063 0.238 0.153 0.3227 0.5891 -0.07 0.9878 0.1559 0.246843247 Phenylpropanoic Hydroxyphenyll Acids actic acid HMDB0000 C03672 16 0.3622 0.58704 0.113 0.4488 0.1693 0.3149 0.116 0.98 0.8424 0.9261 -0.05 0.1466 0.624 0.682266767 HMDB000 Amino Acids Kynurenine 0684 C00328 16 0.0358 0.18259 0.426 1.133 0.0036 0.0165 1.05 1.398 0.9472 0.9666 -0.03 0.3139 0.0055 0.018589645 Amino Acids Aspartic acid HMDB0000 C00049 3 <0.001 0.00192 1.403 2.4534 <0.001 0.0035 1.162 1.623 <0.001 <0.001 1.122 2.2054 0.0001 0.001335961 Aminoadipic HMDB000 Amino Acids acid 0510 C00956 3 0.1834 0.43026 0.296 0.6988 0.2776 0.4316 0.35 0.729 0.4292 0.7299 0.195 0.4944 0.5817 0.667115721 Carbohydrates Glucaric acid HMDB0000 C00818 12 0.486 0.65341 -0.22 0.4936 0.0908 0.2009 0.769 1.123 0.8771 0.9384 5E-04 0.31 0.0643 0.123058223 2-Hydroxy-3- HMDB000 Fatty Acids methylbutyric 0407 - 4 0.9821 0.99235 -0.01 0.0716 0.9508 0.9766 0.07 0.042 0.132 0.3164 0.888 0.7095 0.3659 0.460850622 Pyridines Picolinic acid HMDB0002 C10164 16 0.4379 0.63142 0.226 0.6754 0.0374 0.0993 0.93 0.933 0.3175 0.5891 0.256 0.947 0.1662 0.258444795 ortho- Hydroxyphenyla HMDB000 Benzenoids cetic acid 0669 C05852 12 0.588 0.72678 -0.02 0.3463 <0.001 0.0037 1.614 1.344 0.6888 0.8462 -0.04 0.3361 4E-05 <0.001 Amino Acids Hippuric acid HMDB0000 C01586 12 0.0188 0.12455 -2.53 1.3265 0.7859 0.8547 -0.82 0.498 0.0836 0.2867 -1.52 1.4563 0.0605 0.118118137 HMDB000 Organic Acids Malic acid 0156 C00149 1 0.4258 0.63142 0.163 0.3095 <0.001 0.0037 0.711 1.387 <0.001 0.0066 0.765 1.6304 7E-05 0.001022042 Amino Acids N-Acetyaspartic HMDB0000 C01042 12 0.275 0.53291 -0.56 0.9152 0.0438 0.1105 0.917 0.922 0.6832 0.8462 0.179 0.0024 0.0026 0.010231941 Ethylmethylacet HMDB000 SCFAs ic acid 2176 C18319 14 0.0551 0.23247 0.496 1.1753 0.5095 0.6418 0.302 0.28 0.0442 0.2043 0.56 1.2436 0.0864 0.154840858 Benzenoids Phenylacetic HMDB0000 C07086 1 0.2085 0.45106 0.5 0.8852 0.5254 0.6576 0.311 0.479 0.4379 0.7322 -0.58 0.4238 0.697 0.737827049 Indoles Indole-3- HMDB000 C19837 8 0.0536 0.23247 -0.49 1.2611 0.2069 0.3613 -0.49 0.721 0.049 0.2166 -0.5 1.0488 0.1221 0.204112785 Indoles Indoleacetic HMDB0000 C00954 11 0.0081 0.08483 -0.9 1.2431 0.7859 0.8547 0.111 0.248 0.6423 0.83 0.007 0.3086 0.0168 0.042779448 HMDB000 Organic Acids Fumaric acid 0134 C00122 11 0.0108 0.09813 -0.77 1.9912 0.171 0.3151 0.461 0.744 0.55 0.8109 0.149 0.1311 0.0004 0.002455499 Organic Acids Glutaric acid HMDB0000 C00489 12 0.1593 0.39621 -0.77 0.6319 0.7859 0.8547 -0.01 0.544 0.0614 0.2304 -0.8 0.004 0.1678 0.258882255 HMDB000 Organic Acids Aconitic acid 0958 C02341 12 0.1643 0.39943 -0.27 0.7983 0.6505 0.7752 -0.3 0.668 0.8594 0.9384 -0.03 0.3304 0.61 0.678205771 Phenylpropanoid s Cinnamic acid HMDB0000 C10438 16 0.5733 0.72152 0.057 0.6623 0.0525 0.1274 0.314 1.308 0.7696 0.8902 0.082 0.1137 0.0886 0.157384982 Phenylpropanoic 2- HMDB001 Acids Phenylpropiona 1743 - 15 0.6744 0.78943 -0.17 0.2313 0.0086 0.0324 -0.91 0.246 0.1015 0.2883 -0.45 0.8772 0.0441 0.096395696 Phenylpropanoic Hydrocinnamic Acids acid HMDB0000 C05629 15 0.707 0.79211 0.368 0.4902 0.4134 0.5531 -0.6 0.256 0.1105 0.2883 -0.53 1.0868 0.0788 0.147983398 3- HMDB000 Indoles Indolepropionic 2302 - 7 0.0686 0.26242 -1.1 0.9673 0.007 0.0273 -2.06 0.116 0.2204 0.482 -0.76 1.0969 0.0814 0.148643527 Organic Acids Azelaic acid HMDB0000 C08261 12 0.0043 0.06646 1.061 1.3719 <0.001 0.0026 4.285 1.413 0.1223 0.3005 0.604 1.0539 0.0004 0.002455499 HMDB000 Fatty Acids Sebacic acid 0792 C08277 12 0.0756 0.26378 0.421 1.2193 <0.001 0.0037 2.926 0.773 0.0013 0.013 0.688 1.4755 0.0001 0.001460997 alpha- Organic Acids Ketoisovaleric HMDB0000 C00141 12 0.4855 0.65341 0.116 0.8576 0.0028 0.0144 1.792 1.206 0.9459 0.9666 -0.17 0.5712 0.0044 0.016156797 HMDB000 Organic Acids Ketoleucine 0695 C00233 8 0.3152 0.54459 -0.17 0.3886 0.1507 0.2856 -0.45 0.469 0.088 0.2883 -0.25 0.924 0.62 0.681611159 3-Methy2- Organic Acids oxovaleric acid HMDB0000 C03465 5 0.0546 0.23247 -0.38 0.9724 0.0982 0.2148 -0.4 0.943 0.1015 0.2883 -0.42 0.8101 0.1734 0.26429579 Phenylpyruvic HMDB000 Benzenoids acid 0205 C00166 10 0.0614 0.24425 0.62 1.3036 0.0136 0.0459 0.572 1.38 0.6678 0.8462 -0.07 0.3372 0.0087 0.026675754 Fatty Acids Methylmalonic HMDB0000 C02170 11 0.1004 0.30609 -0.32 1.1855 0.6075 0.7372 0.051 0.426 0.9824 0.9873 0.033 0.1772 0.0812 0.148643527 2- HMDB000 Amino Acids Hydroxyglutaric 0606 C01087 1 0.1223 0.3428 0.449 0.3595 0.0022 0.0114 0.98 1.403 0.0094 0.0603 0.863 1.3835 0.0013 0.00612856 Amino Acids Glycine HMDB0000 C00037 14 0.1223 0.3428 0.372 1.0326 0.4141 0.5531 0.132 0.507 0.0186 0.1086 0.298 1.1063 0.105 0.181412743 Guanidoacetic HMDB000 Organic Acids acid 0128 C00581 8 0.0015 0.03043 -0.75 1.742 <0.001 0.0037 -0.67 1.629 0.0013 0.013 -0.79 1.9507 0.0022 0.009123449 Amino Acids Citrulline HMDB0000 C00327 13 0.0067 0.077 -0.59 1.7025 0.0233 0.0672 -0.49 1.342 0.2564 0.5316 -0.28 0.3809 0.026 0.061379059 HMDB000 Carbohydrates Galactonic acid 0565 C00880 4 0.2733 0.53291 0 0.5973 1 1 0 0.203 0.5398 0.8109 0.017 0.914 0.3973 0.492960325 Carbohydrates Gluconolactone HMDB0000 C00198 12 0.0125 0.10419 0.269 1.2912 <0.001 0.0018 0.935 0.846 0.007 0.0533 0.138 1.1524 0.0001 0.001248639 HMDB000 Organic Acids Glycolic acid 0115 C00160 9 0.5321 0.69793 0.102 0.4281 0.7345 0.8319 -0.06 0.401 0.3114 0.5891 -0.17 0.9779 0.2111 0.297870491 Amino Acids alpha- HMDB0000 C02356 14 0.5208 0.69093 -0.04 0.4167 0.1037 0.2219 -0.42 1.033 0.2564 0.5316 -0.13 0.2412 0.0649 0.123058223 HMDB000 Carbohydrates Glyceric acid 0139 C00258 3 0.0015 0.03043 0.784 2.0707 <0.001 <0.001 0.886 2.061 <0.001 <0.001 0.786 2.1064 0.0004 0.002455499 Amino Acids Proline HMDB0000 C00148 4 0.0349 0.18259 -0.35 1.3856 0.7825 0.8547 -0.05 0.285 0.0527 0.2194 0.318 1.084 0.0016 0.007348811 HMDB000 Amino Acids N-Acetylglycine 0532 - 16 0.2204 0.46666 0.171 0.8397 0.2115 0.3628 0.196 0.986 0.6109 0.8214 -0.09 0.1057 0.1552 0.246843247 Amino Acids Pipecolic acid HMDB0000 C00408 15 0.7402 0.81835 0.027 0.5135 0.0512 0.1258 0.326 1.352 0.1015 0.2883 -0.37 0.6057 0.015 0.039769314 HMDB000 Organic Acids Erythronic acid 0613 - 3 0.2564 0.51545 0.223 0.8471 0.4042 0.5531 0.095 0.469 0.8771 0.9384 -0.08 0.1394 0.6925 0.736906462 Amino Acids N-Acetylserine HMDB0002 - 1 0.3775 0.59691 0.043 0.6044 <0.001 0.0037 0.386 1.621 0.0551 0.2194 0.071 0.7795 0.0009 0.004525869 HMDB000 Organic Acids Shikimic acid 3070 C00493 1 0.4572 0.64653 0.006 1.062 <0.001 <0.001 0.03 1.443 0.6527 0.838 0.002 0.8312 0.0046 0.016483381 Amino Acids N- HMDB0006 - 11 0.3333 0.5559 0 0.8695 0.6005 0.7372 0.003 0.32 0.982 0.9873 8E-04 0.3624 0.5862 0.667115721 HMDB000 Organic Acids Quinic acid 3072 C00296 11 0.6109 0.73675 0.002 0.9231 0.2953 0.4452 0.017 0.035 0.0504 0.2182 0.03 0.1009 0.1319 0.218740682 Carbohydrates N- HMDB0000 C19910 12 0.0173 0.1231 0.185 1.2763 <0.001 <0.001 1.108 1.938 <0.001 0.0026 0.339 1.5079 3E-07 <0.001 HMDB000 SCFAs Acetic acid 0042 C00033 9 0.0756 0.26378 0.384 1.2805 0.7399 0.8319 -0.13 0.288 0.1115 0.2883 -0.41 0.9916 0.0056 0.018589645 Amino Acids Valine HMDB0000 C00183 12 0.558 0.70728 -0.08 0.3557 0.9759 0.9809 -0.05 0.312 0.7081 0.8592 -0.04 0.3937 0.8852 0.898727628 Amino Acids Pyroglutamic HMDB000 C01879 1 <0.001 0.00156 1.01 2.1727 <0.001 <0.001 1.386 1.881 <0.001 <0.001 1.134 2.3065 6E-06 <0.001 Amino Acids 5- HMDB0001 C00430 1 0.2758 0.53291 0.099 0.4984 0.0045 0.0203 0.383 1.413 0.0682 0.2467 0.239 0.8973 0.0135 0.037174896 HMDB000 Carbohydrates Glucose 0122 C00221 9 0.035 0.18259 0.407 1.4496 0.6505 0.7752 -0.07 0.282 0.001 0.0115 -0.79 1.8431 8E-05 0.001022042 Carbohydrates Maltose/Lactos - - 12 0.1015 0.30609 0.675 1.235 <0.001 <0.001 2.31 0.511 0.0043 0.0346 1.303 1.9046 3E-06 <0.001 HMDB000 Carbohydrates Maltotriose 1262 C01835 1 0.2851 0.54041 0 0.4261 0.0032 0.0159 0.61 1.214 0.0281 0.1514 0.296 1.2114 8E-05 0.001022042 Organic Acids 3- HMDB0000 C01089 9 0.3628 0.58704 0.019 0.9704 0.4134 0.5531 -1.15 0.367 0.1223 0.3005 -1.19 0.7464 0.0556 0.114158789 HMDB000 Amino Acids Methionine 0696 C00073 5 0.5527 0.70505 -0.09 0.461 0.6333 0.7638 -0.09 0.348 0.5208 0.8034 -0.08 0.179 0.8363 0.862263386 Benzoic acids 4- HMDB0001 D06890 10 0.4184 0.63082 0.015 1.0061 0.0575 0.1378 0.027 0.961 0.7191 0.8621 0.007 0.3967 0.3988 0.492960325 alpha- HMDB000 Organic Acids Hydroxyisobutyr 0729 - 16 0.4005 0.61311 0.307 0.6835 0.0162 0.052 0.962 1.453 0.5879 0.8182 0.231 0.4005 0.0226 0.055453445 Organic Acids 2- HMDB0000 C05984 10 <0.001 0.00156 0.927 1.8588 0.0056 0.0243 0.836 1.476 0.0144 0.0866 0.496 1.1065 0.0002 0.001896725 SCFAs 3- HMDB000 - 16 0.0108 0.09813 0.152 1.1381 0.0022 0.0114 0.412 1.481 0.8079 0.9084 -0.08 0.119 0.0007 0.003514111 Carbohydrates Glutaconic acid HMDB0000 C02214 12 0.6573 0.7833 -0.17 0.4907 0.0022 0.0114 0.656 1.181 0.1841 0.4117 0.439 0.679 0.0004 0.002455499 HMDB000 Amino Acids Isoleucine 0172 C00407 11 0.2921 0.5432 -0.23 0.6572 0.6075 0.7372 0.04 0.415 0.3281 0.5936 0.174 0.4879 0.15 0.242747664 Amino Acids Leucine HMDB0000 C00123 1 0.2231 0.46728 0.219 0.7753 0.1896 0.3369 0.294 0.908 0.0909 0.2883 0.278 0.929 0.4235 0.520239055 HMDB000 Carbohydrates Xylose 0098 C00181 3 0.0051 0.07249 1.02 1.8583 <0.001 0.0037 0.838 1.316 0.0037 0.0319 0.599 1.2375 0.0037 0.013861781 Carbohydrates Ribulose HMDB0000 C00309 1 0.1402 0.38217 0.163 0.7683 <0.001 <0.001 0.722 1.514 <0.001 <0.001 0.534 1.9111 2E-06 <0.001 Carbohydrates Xylulose HMDB000 C00310 1 0.058 0.23552 0.215 0.9864 <0.001 0.0035 1.033 1.383 <0.001 <0.001 0.496 1.644 4E-06 <0.001 Carbohydrates Rhamnose HMDB0000 C00507 10 0.0126 0.10419 0.599 1.3382 0.022 0.0666 0.564 1.268 0.5801 0.813 -0.21 0.117 0.029 0.066152981 HMDB000 Carbohydrates beta-Fucose 3081 C02095 12 0.4246 0.63142 -0.02 0.3349 0.5532 0.6838 0.003 0.802 0.2297 0.4967 -0.02 0.3279 0.2631 0.358553093 Carbohydrates Fructose HMDB0000 C02336 16 0.0188 0.12455 0.718 0.362 <0.001 0.0019 2.252 1.201 0.0022 0.0208 1.418 0.4771 8E-05 0.001022042
N- HMDB000 Carbohydrates Acetyglucosami 0215 C00140 12 0.8741 0.92245 -0.07 0.6856 <0.001 0.0035 0.519 1.562 0.1208 0.3005 0.176 0.7617 0.0013 0.00612856 SCFAs Propanoic acid HMDB0000 C00163 10 0.0069 0.077 0.683 1.5451 0.0268 0.0751 0.548 0.985 0.2654 0.5389 -0.34 0.7249 0.0004 0.002455499 HMDB000 Amino Acids Norleucine 1645 C01933 1 0.1646 0.39943 0.257 0.8904 0.1179 0.247 0.198 0.923 0.0587 0.2251 0.315 1.0363 0.3431 0.443400159 Phenols Homovanillic HMDB0000 C05582 12 0.6744 0.78943 -0.04 0.2518 0.2604 0.4081 0.077 0.9 0.6744 0.8462 0.011 0.0455 0.3395 0.441526714 HMDB000 Amino Acids Tryptophan 0929 C00078 5 0.0327 0.18259 -0.38 1.4182 0.0372 0.0993 -0.39 1.069 0.4663 0.7545 -0.1 0.4088 0.0201 0.04991134 SCFAs Butyric acid HMDB0000 C00246 9 0.1223 0.3428 0.205 0.9242 0.4134 0.5531 0.109 0.399 0.3993 0.691 -0.25 0.7767 0.0535 0.110860503 HMDB000 SCFAs Isobutyric acid 1873 C02632 12 0.9472 0.97157 -0.13 0.2896 0.0225 0.0666 2.549 1.208 0.9472 0.9666 -0.2 0.2364 0.0131 0.036691375 Benzenoids Mandelic acid HMDB0000 C01984 12 0.3175 0.54459 0.022 1.015 <0.001 0.0013 0.797 0.934 0.1115 0.2883 0.044 0.6183 0.0006 0.003120262 HMDB000 Organic Acids Malonic acid 0691 C00383 14 0.3869 0.59691 -0.35 0.0219 0.2351 0.3835 -0.26 0.366 0.7402 0.8716 0.122 0.1794 0.7401 0.779270562 Amino Acids N- HMDB0006 C04148 1 0.8424 0.90125 0.044 0.2511 0.2875 0.4368 0.821 0.618 0.2962 0.5722 -1.07 0.3927 0.2149 0.301198836 HMDB000 Carbohydrates Tartaric acid 0956 C00898 1 0.3175 0.54459 2.328 0.5763 0.007 0.0273 4.743 1.141 0.0922 0.2883 2.684 0.6213 0.0293 0.066152981 SCFAs Isovaleric acid HMDB0000 C08262 14 0.0682 0.26242 0.483 1.181 0.5468 0.6801 0.194 0.234 0.0551 0.2194 0.521 1.2594 0.0807 0.148643527 HMDB000 SCFAs Pentanoic acid 0892 C00803 15 0.412 0.62579 0.133 0.7092 0.2604 0.4081 0.351 0.599 0.2631 0.5389 -0.42 1.0609 0.0246 0.059511486 Pyridines N- HMDB0003 - 3 0.4647 0.64663 0.896 0.9049 0.7399 0.8319 0.312 0.42 0.5801 0.813 -0.27 0.4694 0.6136 0.678389706 Phenylpropanoic Phenyllactic HMDB000 Acids acid 0779 C01479 2 0.2062 0.45106 1.336 0.7125 0.0012 0.0076 2.147 1.738 0.2875 0.5609 1.192 0.6793 0.0071 0.022838158 Organic Acids Oxalic acid HMDB0002 C00209 9 0.0311 0.18193 0.928 1.5695 0.8534 0.9082 -0.03 0.203 0.3568 0.6339 -0.35 0.3714 0.0248 0.059511486 Organic Acids Maleic acid HMDB000 C01384 11 <0.001 0.01741 -0.88 2.3177 0.0872 0.1973 0.428 0.934 0.912 0.9502 -0.05 0.0033 7E-06 <0.001 Fatty Acids Itaconic acid HMDB0002 C00490 12 0.6043 0.73675 0.074 0.071 0.8271 0.891 -0.09 0.723 0.9092 0.9502 -0.03 0.822 0.9672 0.967235285 HMDB000 Organic Acids Citraconic acid 0634 C02226 7 0.0897 0.28775 -0.08 0.9995 0.9279 0.9617 0 0.306 0.1005 0.2883 -0.08 0.6193 0.0599 0.118107903 Organic Acids Methylsuccinic HMDB0001 - 12 0.8424 0.90125 -0.08 0.0082 0.347 0.4968 0.168 0.65 0.3175 0.5891 -0.18 0.1733 0.2194 0.305319709 HMDB000 Organic Acids Adipic acid 0448 C06104 12 0.3327 0.5559 0.201 0.0736 0.0329 0.0896 1.917 0.711 0.1201 0.3005 0.883 0.1561 0.0503 0.107711735 Fatty Acids Methylglutaric HMDB0000 - 10 0.088 0.28775 0.205 1.1655 0.1796 0.3249 0.174 0.76 0.841 0.9261 0.03 0.1309 0.269 0.364179211 HMDB000 Benzoic acids Phthalic acid 2107 C01606 16 0.615 0.73723 0.01 0.4245 0.0512 0.1258 0.037 0.61 0.9984 0.9984 5E-05 0.1007 0.2792 0.372872578 Organic Acids Pimelic acid HMDB0000 C02656 12 0.207 0.45106 14.13 0.344 0.0096 0.0353 17.53 1.073 0.1242 0.3015 15.41 0.754 0.02 0.04991134 3-Methyladipic HMDB000 Fatty Acids acid 0555 - 1 0.3138 0.54459 0.431 0.3207 0.1693 0.3149 0.687 0.863 0.5801 0.813 0.091 0.4686 0.5188 0.629509226 SCFAs 2- HMDB0031 - 16 0.0754 0.26378 0.365 0.889 <0.001 0.0019 0.981 1.757 0.1099 0.2883 0.311 1.0539 6E-06 <0.001 SCFAs 3- HMDB003 - 8 0.1461 0.38268 -0.69 0.8143 0.2115 0.3628 -0.89 0.663 0.0922 0.2883 -0.95 0.8911 0.2402 0.329714158 SCFAs Isocaproic acid HMDB0000 - 13 0.2564 0.51545 -0.19 0.6802 0.2875 0.4368 -0.29 0.247 0.9824 0.9873 0 0.0362 0.3552 0.456038704 HMDB000 SCFAs Caproic acid 0535 C01585 9 0.3096 0.54459 0.183 0.7203 0.8302 0.891 0.038 0.079 0.882 0.9386 -0.03 0.4599 0.5259 0.630450514 Organic Acids Suberic acid HMDB0000 C08278 12 0.3338 0.5559 0.027 0.141 0.0246 0.0701 1.986 1.264 0.1105 0.2883 0.497 0.7625 0.0582 0.116892422 HMDB000 Organic Acids Citric acid 0094 C00158 12 0.1957 0.44265 -0.26 0.7875 0.6947 0.8085 -0.3 0.66 0.5501 0.8109 -0.33 0.4163 0.6723 0.723200219 Organic Acids Isocitric acid HMDB0000 C00311 12 0.7085 0.79211 -0.05 0.4303 0.3164 0.4664 0.025 0.684 0.3397 0.609 -0.26 0.4352 0.272 0.365671548 HMDB000 Fatty Acids Heptanoic acid 0666 C17714 6 0.1733 0.4154 -0.34 0.2424 0.2257 0.3807 -0.33 0.81 0.0454 0.2055 -0.5 1.3645 0.2012 0.286060167
Organic Acids Pyruvic acid HMDB0000 C00022 6 0.1881 0.43524 -0.48 0.2487 0.1783 0.3249 -0.37 0.768 <0.001 <0.001 -1.57 2.3614 0.0002 0.001460997 HMDB000 Bile Acids TCDCA 0951 C05465 16 0.1184 0.3428 2.22 0.3909 <0.001 0.005 3.623 1.258 0.9092 0.9502 0.45 0.0952 0.0004 0.002455499 Bile Acids aMCA HMDB0000 C17647 4 0.1461 0.38268 -0.05 0.8295 0.4769 0.6203 -0.03 0.752 0.5998 0.8214 -0.05 0.515 0.6028 0.673879841 HMDB000 Bile Acids bMCA 0865 - 4 0.1461 0.38268 -0.05 0.8295 0.4769 0.6203 -0.03 0.752 0.5998 0.8214 -0.05 0.515 0.6028 0.673879841 Bile Acids HCA HMDB0000 - 4 0.6686 0.78943 0 0.5618 0.78 0.8547 0.021 0.168 0.3959 0.691 -0.18 0.614 0.5258 0.630450514 HMDB000 Bile Acids CA 0619 C00695 4 0.0144 0.10987 -0.87 1.8791 0.1896 0.3369 -0.74 0.795 0.3628 0.639 -0.61 0.4379 0.1753 0.26429579 Organic Acids Oxoglutaric acid HMDB0000 C00026 10 0.0442 0.20434 0.891 1.5354 <0.001 <0.001 0.879 1.487 0.3175 0.5891 0.106 0.7912 0.0008 0.004246796 HMDB000 Bile Acids GCA 0138 C01921 12 0.7696 0.8415 0.166 0.2691 0.0209 0.0649 1.556 0.728 0.7357 0.8715 -0.16 0.5175 0.0162 0.041832276 Fatty Acids Octanoic acid HMDB0000 C06423 12 0.2786 0.53311 -0.17 0.5476 0.0688 0.1592 2.131 1.02 0.0977 0.2883 -0.25 1.2516 0.0093 0.02776942 HMDB000 Bile Acids bUDCA 0686 C17662 4 0.4304 0.63142 -0.33 0.9242 0.2172 0.3695 -0.51 0.392 0.6858 0.8462 0.558 0.4808 0.2832 0.375735466 Bile Acids bHDCA HMDB0000 - 6 0.9816 0.99235 -0.06 0.0858 0.386 0.5409 -0.12 0.723 0.5291 0.81 -0.01 1.0778 0.6375 0.693274003 HMDB000 Bile Acids UDCA 0946 C07880 2 0.2164 0.46303 -0.61 1.0712 0.9754 0.9809 -0.09 0.559 0.8396 0.9261 0.141 0.5293 0.59 0.667115721 Bile Acids bDCA - - 8 0.4849 0.65341 0.008 0.8571 0.1262 0.2563 -0.09 1.01 0.0735 0.2612 -0.06 1.4472 0.1057 0.181412743 HMDB000 Bile Acids CDCA 0518 C02528 13 0.0037 0.0642 -0.97 1.9874 0.0439 0.1105 -1.33 0.75 0.5801 0.813 -0.2 0.0776 0.0098 0.028794967 Bile Acids DCA HMDB0000 C04483 8 0.0442 0.20434 -0.7 1.4687 0.0129 0.045 -1.57 1.445 0.0081 0.0597 -0.94 2.0178 0.008 0.025358738 HMDB000 Bile Acids isoDCA 2536 C17661 14 0.7639 0.83983 0.091 0.2942 0.2319 0.3835 -0.04 1.047 0.6796 0.8462 0.081 0.2817 0.1603 0.251163974 Fatty Acids Nonanoic acid HMDB0000 C01601 16 0.7049 0.79211 0.099 0.3487 0.0228 0.0666 0.768 1.153 0.8017 0.9084 -0.07 0.4145 0.0049 0.017390693 HMDB000 Fatty Acids Decanoic acid 0511 C01571 12 0.4379 0.63142 -0.31 0.5643 0.0225 0.0666 3.266 1.14 0.2758 0.5435 -0.57 0.0595 0.005 0.017390693 Fatty Acids Undecylenic HMDB0033 C13910 6 0.5435 0.70505 -0.13 0.0302 <0.001 0.0027 -2.76 1.819 0.0032 0.0292 -1.6 1.9347 0.0005 0.003085233 HMDB000 Bile Acids GCDCA 0637 C05466 1 0.3869 0.59691 0.242 0.5814 0.007 0.0273 0.897 1.137 0.6109 0.8214 0.106 0.7113 0.0649 0.123058223 Bile Acids GDCA HMDB0000 C05464 6 1 1 -0.02 0.2832 0.2059 0.3613 -0.53 0.692 0.1101 0.2883 -0.49 1.4866 0.3591 0.458136424 HMDB000 Fatty Acids Undecanoic acid 0947 C17715 16 0.5331 0.69793 0.232 0.6776 0.0768 0.1756 0.722 0.902 0.7258 0.8648 -0.15 0.3722 0.0452 0.097810062 Fatty Acids 5-Dodecenoic HMDB0000 - 8 0.0442 0.20434 -0.98 1.0462 0.0022 0.0114 -1.6 0.837 <0.001 0.0112 -1.51 1.8089 0.0083 0.025661803 HMDB000 Fatty Acids Dodecanoic acid 0638 C02679 11 0.0275 0.17109 -0.73 1.3143 0.1335 0.2606 -0.79 0.22 0.1115 0.2883 -0.86 0.0644 0.1841 0.269434721 Fatty Acids 12-Tridecenoic - - 12 0.5208 0.69093 0.169 0.1695 0.347 0.4968 0.21 0.37 0.6423 0.83 0.081 0.4835 0.8164 0.846208063 HMDB000 Fatty Acids Tridecanoic acid 0910 C17076 12 0.4751 0.65341 0.235 0.6537 0.9754 0.9809 0.023 0.472 0.4583 0.7545 0.185 0.2829 0.587 0.667115721 Fatty Acids Myristoleic acid HMDB0002 C08322 5 0.0846 0.2854 -0.79 1.0513 0.0688 0.1592 -1.06 0.723 0.2181 0.482 -0.51 1.1699 0.1922 0.279234018 Myristelaidic HMDB006 Fatty Acids acid 2248 - 12 0.3107 0.54459 -1.17 0.5432 0.1012 0.2189 -2 0.459 0.0339 0.1644 -1.14 1.3806 0.1796 0.268676669 Fatty Acids Ricinoleic acid HMDB0034 C08365 7 0.1518 0.38936 -0.33 0.9298 0.9543 0.9766 -0.02 0.027 0.1115 0.2883 -0.42 1.2999 0.305 0.399256464 Fatty Acids 12- HMDB006 - 9 0.2564 0.51545 0.171 1.0626 0.3164 0.4664 0.084 0.921 0.5196 0.8034 0.134 0.3776 0.4933 0.602242014 Fatty Acids Myristic acid HMDB0000 C06424 12 0.9824 0.99235 -0.14 0.2086 0.4865 0.6205 0.322 0.57 0.8079 0.9084 -0.11 0.0301 0.7881 0.821085916 Pentadecanoic HMDB000 Fatty Acids acid 0826 C16537 12 0.5801 0.72152 0.132 0.5753 0.2351 0.3835 0.346 0.593 0.912 0.9502 -0.07 0.6092 0.5715 0.665242357 Fatty Acids Palmitoleic acid HMDB0003 C08362 15 0.733 0.81488 0.116 0.4068 0.4895 0.6205 0.28 0.504 0.568 0.813 -0.19 0.576 0.5724 0.665242357 Fatty Acids 10Z- HMDB006 - 16 0.6792 0.79037 0.175 0.5127 0.4134 0.5531 0.645 0.704 0.5438 0.8109 -0.14 0.2084 0.5401 0.636034564 Fatty Acids alpha-Linolenic HMDB0001 C06427 15 0.7739 0.84154 0.075 0.2695 0.4865 0.6205 0.314 0.478 0.1593 0.3729 -0.74 1.1444 0.1363 0.224197294 gamma- HMDB000 Fatty Acids Linolenic acid 3073 C06426 16 0.3397 0.55864 0.918 0.7207 0.0439 0.1105 1.29 1.133 0.707 0.8592 0.101 0.638 0.0288 0.066152981 Fatty Acids Linoleic acid HMDB0000 C01595 10 0.1539 0.38936 0.422 1.1452 0.1198 0.2483 0.6 0.865 0.3215 0.5891 -0.32 0.8895 0.0535 0.110860503 HMDB000 Fatty Acids Linoelaidic acid 6270 - 15 0.697 0.79211 0.183 0.5299 0.125 0.2563 0.923 0.872 0.2404 0.5143 -0.66 1.1165 0.0563 0.114407548 Fatty Acids EPA HMDB0001 C06428 3 0.0895 0.28775 4.617 1.4092 0.0625 0.1481 3.958 0.833 0.0316 0.157 4.138 1.0327 0.1475 0.240539662 HMDB000 Fatty Acids Arachidonic acid 1043 C00219 10 0.2038 0.45106 0.359 1.2004 0.1161 0.2458 0.369 1.095 0.6158 0.8224 0.102 0.4564 0.3734 0.467356495 8,11,14- Fatty Acids Eicosatrienoic HMDB0002 C03242 10 0.0344 0.18259 0.936 1.5072 0.0051 0.0227 1.284 1.578 0.1815 0.4105 0.535 0.7195 0.0141 0.038524316 HMDB000 Fatty Acids DHA 2183 C06429 14 0.1115 0.3313 0.768 1.4623 0.957 0.9766 -0.02 0.143 0.1699 0.3886 0.428 0.7454 0.1821 0.269434721 Fatty Acids DPA HMDB0006 C16513 10 0.3869 0.59691 0.889 0.9398 0.2351 0.3835 0.484 0.681 0.4647 0.7545 0.2 0.2561 0.6817 0.729349363 HMDB000 Fatty Acids DPAn-6 1976 - 14 0.4779 0.65341 0.362 0.7475 0.7226 0.8312 0.177 0.364 0.5501 0.8109 -0.01 0.515 0.9029 0.912098904 Fatty Acids Adrenic acid HMDB0002 C16527 16 0.238 0.49329 0.725 0.8888 0.0106 0.0376 1.268 1.392 0.2758 0.5435 0.326 0.5394 0.0597 0.118107903 HMDB000 Organic Acids Succinic acid 0254 C00042 11 0.0988 0.30609 -0.5 1.1445 0.7399 0.8319 -0.15 0.555 0.631 0.83 0.118 0.0972 0.0379 0.08387254 Organic Acids Citramalic acid HMDB0000 C00815 12 0.4379 0.63142 -0.2 0.1546 0.8801 0.9316 -0.01 0.611 0.4869 0.7751 0.145 0.4847 0.575 0.665242357 Heptadecanoic HMDB000 Fatty Acids acid 2259 - 16 0.707 0.79211 0.514 0.6317 0.0908 0.2009 1.279 1.196 0.8771 0.9384 -0.14 0.097 0.1828 0.269434721 Fatty Acids Oleic acid HMDB0000 C00712 10 0.1338 0.36983 0.345 1.1887 0.1507 0.2856 0.338 0.995 0.7965 0.9084 -0.06 0.1768 0.0854 0.154481889 Fatty Acids 10Z- HMDB001 - 12 0.6109 0.73675 -0.38 0.3217 0.4865 0.6205 0.208 0.772 0.6109 0.8214 -0.24 0.0924 0.5401 0.636034564 Carnitines Carnitine HMDB0000 C00318 15 0.9147 0.94804 0.029 0.15 0.3004 0.4494 0.282 0.73 0.4855 0.7751 -0.16 0.4413 0.3648 0.460850622 HMDB000 Carnitines Acetylcarnitine 0201 C02571 15 0.8783 0.92245 -0.03 0.1384 0.4491 0.5959 0.106 0.799 0.0756 0.2638 -0.53 0.7293 0.0898 0.158226749 Carnitines Propionylcarniti HMDB0000 C03017 16 0.3696 0.59308 0.3 0.3817 0.0059 0.0248 0.907 1.494 0.7572 0.8863 -0.08 0.343 0.0051 0.017486838 Malonylcarnitin HMDB000 Carnitines e 2095 - 12 0.1921 0.43933 -0.06 1.0785 0.0319 0.0882 0.168 1.16 0.7739 0.8902 -0.02 0.0695 0.0101 0.029087 Carnitines Butyrylcarnitine HMDB0002 C02862 15 0.6109 0.73675 -0.04 0.5046 0.1335 0.2606 0.463 0.842 0.0275 0.1514 -0.3 0.6959 0.0159 0.041619728 2- HMDB000 Carnitines Methylbutyroylc 0378 - 7 0.0243 0.15591 -0.17 1.4797 0.347 0.4968 0.023 0.027 0.1461 0.3462 -0.16 1.2195 0.0031 0.011844061 Carnitines Valerylcarnitine HMDB0013 - 15 0.707 0.79211 -0.12 0.097 0.1335 0.2606 0.5 0.678 0.6423 0.83 -0.05 0.6749 0.1989 0.28471129 Isovelarylcarniti HMDB000 Carnitines ne 0688 - 15 0.707 0.79211 -0.12 0.097 0.1335 0.2606 0.5 0.678 0.6423 0.83 -0.05 0.6749 0.1989 0.28471129 3- Hydroxylisovale Carnitines rylcarnitine - - 12 0.0756 0.26378 0.176 0.7897 <0.001 0.0019 0.624 1.551 0.0549 0.2194 0.177 1.0826 0.0004 0.002455499 Glutarylcarnitin HMDB001 Carnitines e 3130 - 13 0.007 0.077 -1.1 1.9659 0.2514 0.4068 -0.35 0.618 0.4923 0.7775 -0.47 0.4844 0.0102 0.029087 Carnitines Hexanylcarnitin HMDB0000 - 7 0.0144 0.10987 -0.36 1.5109 0.2604 0.4081 -0.22 0.255 <0.001 <0.001 -0.61 2.1799 0.0003 0.002455499 HMDB006 Carnitines Adipoylcarnitine 1677 - 15 0.5501 0.70505 -0.09 0.3823 0.7859 0.8547 -0.07 0.779 0.0125 0.0777 -0.31 0.7721 0.1076 0.182961667 Carnitines Octanoylcarniti HMDB0000 C02838 8 <0.001 0.01308 -1.19 1.8693 0.0156 0.0509 -1.55 0.994 <0.001 0.0011 -2.25 2.3595 0.0002 0.001896725 Decanoylcarniti HMDB000 Carnitines ne C10 0651 - 8 <0.001 0.01124 -1.04 1.929 0.0106 0.0376 -1.31 1.309 <0.001 <0.001 -1.41 2.4164 0.0003 0.002266751 Carnitines Lauroylcarnitine HMDB0002 - 8 0.0561 0.23247 -0.32 1.5984 <0.001 0.003 -1.73 1.583 <0.001 0.0069 -2.31 2.0478 0.0012 0.005766773 Palmitoylcarniti HMDB000 Carnitines ne 0222 C02990 11 0.0808 0.2774 -0.64 1.219 0.9005 0.9431 -0.05 0.111 0.9382 0.9666 0.026 0.0232 0.2399 0.329714158 Carnitines Oleylcarnitine HMDB0005 - 1 0.441 0.63143 0.275 0.4818 0.0086 0.0324 1.18 1.505 0.035 0.166 0.599 1.3856 0.0143 0.038552004 HMDB000 Carnitines Linoleylcarnitine 6469 - 1 0.1838 0.43026 -0.81 0.5237 0.0132 0.0452 1.029 1.236 0.0588 0.2251 0.669 0.8809 0.0024 0.009752072 Carnitines Stearylcarnitine HMDB0000 - 2 0.8424 0.90125 -0.27 0.3862 0.1507 0.2856 0.181 1.181 0.0682 0.2467 0.458 1.286 0.1149 0.193855084 Bile Acids NorCA - - 1 0.0039 0.0642 0.011 1.2554 <0.001 0.0041 0.152 1.089 0.0229 0.1303 0 0.5068 0.002 0.008598336 Fatty Acids 2,2- - - 6 0.3175 0.54459 -0.02 0.3565 0.2604 0.4081 -0.03 0.602 0.5801 0.813 0.004 0.7027 0.6648 0.718999439 Table S4. Characteristics of validation cohort patients infected with COVID-19 at admission according to disease severity Characteristics Mild (n=46) Recovery (n=22) Severe (n=22) P Age, years 49.85(45.85-53.85) 51.14(45.00-57.27) 65.73(60.55-70.90) <0.001 Gender Male 22(47.8%) 11(50.0%) 13(59.1%) 0.874 Female 24(52.2%) 11(50.0%) 9(40.9%)
Coexisting disordera 27(58.7%) 10(45.5%) 9(40.9%) 0.324 Clinical signs and symptoms Fever 38(82.6%) 15(68.2%) 18(81.8%) 0.366 Cough 36(78.3%) 13(59.1%) 12(54.5%) 0.089 Chilly 10(21.7%) 6(27.3%) 0(0.0%) 0.037 Myalgia 14(30.4%) 2(9.1%) 0(0.0%) 0.004 Fatigue 22(47.8%) 1(4.5%) 4(18.2%) <0.001 Rhinorrhoea 10(21.7%) 0(0.0%) 0(0.0%) 0.005 Shortness of breath 4(8.7%) 1(4.5%) 19(86.4%) <0.001 Sore throat 10(21.7%) 0(0.0%) 2(9.1%) 0.038 Diarrhea 0(0.0%) 1(4.5%) 0(0.0%) 0.210 Chest CT findings Ground-glass opacity 24(52.2%) 17(77.3%) 21(95.5%) 0.001 Local mottling shadow 4(8.7%) 2(9.1%) 0(0.0%) 0.353 Bilateral mottling shadow 19(41.3%) 7(31.8%) 4(18.2%) 0.164 Laboratory parameters Leucocytes(×10⁹ /L; NR:3.5-9.5) 6.41(5.78-7.07) 4.91(4.07-5.76) 6.60(5.01-8.21) 0.050 Lymphocytes(×10⁹ /L; 1.38(1.15-1.61) 0.77(0.61-0.94) NR:1.1-3.2) 1.48(1.04-1.93) 0.006 Neutrophils(×10⁹ /L; NR:1.8-6.3) 3.60(3.06-4.15) 3.16(2.74-3.59) 3.54(2.81-4.27) 0.570 Platelets(×10⁹ /L; 183.92(165.24-202.60) 180.32(151.46-209.17) NR:125.0-350.0) 175.27(150.12-200.42) 0.864 HGB(g/L; NR:130.0-175.0) 126.44(119.35-133.54) 124.63(108.37-140.89) 126.68(118.66-134.70) 0.958
APTT(s; NR:21.0-37.0)b 39.10(37.81-40.39) 40.04(38.07-42.02) 40.35(38.57-42.12) 0.523
PT(s; NR:10.5-13.5)b 13.87(13.57-14.18) 14.30(13.49-15.10) 13.93(13.25-14.61) 0.447 b D-dimer(mg/L; NR:0-500) 2063.9(1189.3-2938.6) 1867.4(1175.4-2559.5) 1600.7(1365.4-1835.9) 0.816 Albumin (g/L; NR:40.0-55.0) 38.79(36.85-40.73) 38.47(36.26-40.68) 35.41(33.44-37.39) 0.071 ALT (U/L; NR:9.0-50.0) 37.41(22.91-51.92) 37.32(26.02-48.62) 50.70(22.08-79.31) 0.543 AST (U/L; NR:15.0-40.0) 26.77(22.34-31.20) 37.02(18.77-35.27) 23.95(22.08-25.82) 0.707 TB (μmol/L; NR:0.0-21.0) 15.32(11.53-19.12) 13.35(6.96-19.73) 16.22(12.15-20.29) 0.732 BUN (mmol/L; NR:3.6-9.5) 4.72(3.98-5.46) 4.30(3.31-5.29) 4.35(4.10-4.59) 0.672 Scr (μmol/L; NR:57.0-111.0) 69.78(61.11-78.46) 68.41(49.99-86.83) 69.26(66.07-72.45) 0.984 CK (U/L; NR:50.0-310.0) 79.03(64.33-93.73) 71.12(47.24-95.00) 85.68(67.52-103.84) 0.612 LDH (U/L; NR:120.0-250.0) 218.71(189.48-247.94) 199.36(165.60-233.12) 217.89(195.28-240.50) 0.651 CRP (mg/L; NR:0.0-5.0) 20.13(15.42-24.84) 15.79(10.81-20.76) 16.25(11.07-21.44) 0.377 Abbreviation: HGB, hemoglobin; APTT, activated partial thromboplastin time; PT, prothrombin time; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TB, total bilirubin; BUN, blood urea nitrogen; Scr, serum creatinine; CK, creatine kinase; LDH, lactate dehydrogenase; CRP, C-reactive protein; NR, normal reference. a Including hypertension, type 2 diabetes mellitus, cancer, hyperlipidemia, liver disease and other chronic diseases,b missing for 9 severe group. Table S5. Metabolites quantified in the discovery cohort by targeted metabolomics with FDR<0.05 (related to figure 2-A) Normal VS Mild Normal VS Severe Normal VS Recovery Total Class Name HMDB_ID KEGG_ID P FDR log2FC VIP P FDR log2FC VIP P FDR log2FC VIP P FDR Amino Acids Arginine HMDB0000517 C00062 0.914 0.948 0.02 0.0469 0.0019 0.011 -0.48 1.643 0.0089 0.060 -0.37 1.3098 0.0025 0.0098 Amino Acids Ornithine HMDB0000214 C00077 0.0311 0.18193 0.371 1.5216 <0.001 0.0035 0.981 1.794 <0.001 <0.001 1.56 2.3139 0.00 <0.001 Amino Acids Glutamine HMDB0000641 C00064 0.037 0.185 -0.36 1.4032 0.0019 0.011 -0.62 1.791 0.0043 0.035 -0.48 1.8552 0.0019 0.0082 Amino Acids Glutamic acid HMDB0000148 C00025 <0.001 0.00256 0.82 1.8495 <0.001 <0.001 1.482 2.015 <0.001 <0.001 1.45 2.6133 0.00 <0.001 Amino Acids beta-Alanine HMDB0000056 C00099 0.881 0.922 -0.01 0.3399 0.0439 0.111 0.54 1.32 0.0311 0.157 0.13 0.8346 0.0063 0.0204 Amino Acids GABA HMDB0000112 C00334 <0.001 0.01124 -0.59 2.402 0.019 0.0594 -0.53 1.12 0.0094 0.060 -0.39 1.6741 0.00 0.0081 Amino Acids Creatine HMDB0000064 C00300 0.292 0.543 0.34 0.6911 0.0036 0.016 1.97 1.569 0.2758 0.543 -0.26 0.5015 0.0002 0.0019 Organic Acids Hydroxypropionic acid HMDB0000700 C01013 0.8771 0.92245 -0.13 0.1221 0.016 0.0509 0.484 0.877 0.4369 0.732 -0.12 0.5262 0.01 0.0268 Amino Acids Homocitrulline HMDB0000679 C02427 0.317 0.545 -0.16 1.1381 0.0036 0.016 1.15 1.487 0.7739 0.890 0.16 0.4166 0.0004 0.0025 Organic Acids Lactic acid HMDB0000190 C00186 0.4647 0.64663 0.105 0.5539 <0.001 <0.001 1.238 2.229 <0.001 <0.001 1.16 2.7261 0.00 <0.001 Amino Acids 2-Phenylglycine HMDB0002210 - 0.076 0.264 0.09 0.8204 <0.001 0.003 0.46 1.398 0.0311 0.157 0.08 0.5041 0.0012 0.006 3,4- Phenylpropanoid Dihydroxyhydrocinnami s c acid HMDB0000423 C10447 0.3175 0.54459 -0.5 0.2193 <0.001 0.0019 1.653 1.775 <0.001 <0.001 2.00 2.5133 0.00 <0.001 Amino Acids Asparagine HMDB0000168 C00152 0.011 0.098 -0.34 1.2909 0.8328 0.891 0.08 0.333 0.0094 0.060 0.20 1.3742 0.0001 0.0015 Amino Acids Kynurenine HMDB0000684 C00328 0.0358 0.18259 0.426 1.133 0.004 0.0165 1.05 1.398 0.9472 0.967 -0.03 0.3139 0.01 0.0186 Amino Acids Aspartic acid HMDB0000191 C00049 <0.001 0.002 1.40 2.4534 <0.001 0.003 1.16 1.623 <0.001 <0.001 1.12 2.2054 0.0001 0.0013 ortho- Hydroxyphenylacetic Benzenoids acid HMDB0000669 C05852 0.588 0.72678 -0.02 0.3463 <0.001 0.0037 1.614 1.344 0.6888 0.846 -0.04 0.3361 0.00 <0.001 Organic Acids Malic acid HMDB0000156 C00149 0.426 0.631 0.16 0.3095 <0.001 0.004 0.71 1.387 <0.001 0.007 0.76 1.6304 7E-05 0.001 Amino Acids N-Acetyaspartic acid HMDB0000812 C01042 0.275 0.53291 -0.56 0.9152 0.044 0.1105 0.917 0.922 0.6832 0.846 0.18 0.0024 0.00 0.0102 Indoles Indoleacetic acid HMDB0000197 C00954 0.008 0.085 -0.90 1.2431 0.7859 0.855 0.11 0.248 0.6423 0.830 0.01 0.3086 0.0168 0.0428 Organic Acids Fumaric acid HMDB0000134 C00122 0.0108 0.09813 -0.77 1.9912 0.171 0.3151 0.461 0.744 0.55 0.811 0.15 0.1311 0.00 0.0025 Organic Acids Azelaic acid HMDB0000784 C08261 0.004 0.066 1.06 1.3719 <0.001 0.003 4.29 1.413 0.1223 0.300 0.60 1.0539 0.0004 0.0025 Fatty Acids Sebacic acid HMDB0000792 C08277 0.0756 0.26378 0.421 1.2193 <0.001 0.0037 2.926 0.773 0.0013 0.013 0.69 1.4755 0.00 0.0015
Organic Acids alpha-Ketoisovaleric acid HMDB0000019 C00141 0.485 0.653 0.12 0.8576 0.0028 0.014 1.79 1.206 0.9459 0.967 -0.17 0.5712 0.0044 0.0162 Benzenoids Phenylpyruvic acid HMDB0000205 C00166 0.0614 0.24425 0.62 1.3036 0.014 0.0459 0.572 1.38 0.6678 0.846 -0.07 0.3372 0.01 0.0267 Amino Acids 2-Hydroxyglutaric acid HMDB0000606 C01087 0.122 0.343 0.45 0.3595 0.0022 0.011 0.98 1.403 0.0094 0.060 0.86 1.3835 0.0013 0.0061 Organic Acids Guanidoacetic acid HMDB0000128 C00581 0.0015 0.03043 -0.75 1.742 <0.001 0.0037 -0.67 1.629 0.0013 0.013 -0.79 1.9507 0.00 0.0091 Carbohydrates Gluconolactone HMDB0000150 C00198 0.012 0.104 0.27 1.2912 <0.001 0.002 0.94 0.846 0.007 0.053 0.14 1.1524 0.0001 0.0012 Carbohydrates Glyceric acid HMDB0000139 C00258 0.0015 0.03043 0.784 2.0707 <0.001 <0.001 0.886 2.061 <0.001 <0.001 0.79 2.1064 0.00 0.0025 Amino Acids Proline HMDB0000162 C00148 0.035 0.183 -0.35 1.3856 0.7825 0.855 -0.05 0.285 0.0527 0.219 0.32 1.084 0.0016 0.0073 Amino Acids Pipecolic acid HMDB0000716 C00408 0.7402 0.81835 0.027 0.5135 0.051 0.1258 0.326 1.352 0.1015 0.288 -0.37 0.6057 0.01 0.0398 Amino Acids N-Acetylserine HMDB0002931 - 0.377 0.597 0.04 0.6044 <0.001 0.004 0.39 1.621 0.0551 0.219 0.07 0.7795 0.0009 0.0045 Organic Acids Shikimic acid HMDB0003070 C00493 0.4572 0.64653 0.006 1.062 <0.001 <0.001 0.03 1.443 0.6527 0.838 0.00 0.8312 0.00 0.0165 Carbohydrates N-Acetylneuraminic acid HMDB0000230 C19910 0.017 0.123 0.18 1.2763 <0.001 <0.001 1.11 1.938 <0.001 0.003 0.34 1.5079 3E-07 <0.001 SCFAs Acetic acid HMDB0000042 C00033 0.0756 0.26378 0.384 1.2805 0.740 0.8319 -0.13 0.288 0.1115 0.288 -0.41 0.9916 0.01 0.0186 Amino Acids Pyroglutamic acid HMDB0000267 C01879 <0.001 0.002 1.01 2.1727 <0.001 <0.001 1.39 1.881 <0.001 <0.001 1.13 2.3065 6E-06 <0.001 Amino Acids 5-Aminolevulinic acid HMDB0001149 C00430 0.2758 0.53291 0.099 0.4984 0.004 0.0203 0.383 1.413 0.0682 0.247 0.24 0.8973 0.01 0.0372 Carbohydrates Glucose HMDB0000122 C00221 0.035 0.183 0.41 1.4496 0.6505 0.775 -0.07 0.282 0.001 0.012 -0.79 1.8431 8E-05 0.001 Carbohydrates Maltose/Lactose - - 0.1015 0.30609 0.675 1.235 <0.001 <0.001 2.31 0.511 0.0043 0.035 1.30 1.9046 0.00 <0.001 Carbohydrates Maltotriose HMDB0001262 C01835 0.285 0.540 0.00 0.4261 0.0032 0.016 0.61 1.214 0.0281 0.151 0.30 1.2114 8E-05 0.001 Organic Acids 2-Hydroxybutyric acid HMDB0000008 C05984 <0.001 0.00156 0.927 1.8588 0.006 0.0243 0.836 1.476 0.0144 0.087 0.50 1.1065 0.00 0.0019 SCFAs 3-Hydroxyisovaleric acid HMDB0000754 - 0.011 0.098 0.15 1.1381 0.0022 0.011 0.41 1.481 0.8079 0.908 -0.08 0.119 0.0007 0.0035 Carbohydrates Glutaconic acid HMDB0000620 C02214 0.6573 0.7833 -0.17 0.4907 0.002 0.0114 0.656 1.181 0.1841 0.412 0.44 0.679 0.00 0.0025 Carbohydrates Xylose HMDB0000098 C00181 0.005 0.072 1.02 1.8583 <0.001 0.004 0.84 1.316 0.0037 0.032 0.60 1.2375 0.0037 0.0139 Carbohydrates Ribulose HMDB0000621 C00309 0.1402 0.38217 0.163 0.7683 <0.001 <0.001 0.722 1.514 <0.001 <0.001 0.53 1.9111 0.00 <0.001 Carbohydrates Xylulose HMDB0001644 C00310 0.058 0.236 0.22 0.9864 <0.001 0.003 1.03 1.383 <0.001 <0.001 0.50 1.644 4E-06 <0.001 Carbohydrates Fructose HMDB0000660 C02336 0.0188 0.12455 0.718 0.362 <0.001 0.0019 2.252 1.201 0.0022 0.021 1.42 0.4771 0.00 0.001 Carbohydrates N-Acetyglucosamine HMDB0000215 C00140 0.874 0.922 -0.07 0.6856 <0.001 0.003 0.52 1.562 0.1208 0.300 0.18 0.7617 0.0013 0.0061 SCFAs Propanoic acid HMDB0000237 C00163 0.0069 0.077 0.683 1.5451 0.027 0.0751 0.548 0.985 0.2654 0.539 -0.34 0.7249 0.00 0.0025 Amino Acids Tryptophan HMDB0000929 C00078 0.033 0.183 -0.38 1.4182 0.0372 0.099 -0.39 1.069 0.4663 0.754 -0.10 0.4088 0.0201 0.0499 SCFAs Isobutyric acid HMDB0001873 C02632 0.9472 0.97157 -0.13 0.2896 0.023 0.0666 2.549 1.208 0.9472 0.967 -0.20 0.2364 0.01 0.0367 Benzenoids Mandelic acid HMDB0000703 C01984 0.317 0.545 0.02 1.015 <0.001 0.001 0.80 0.934 0.1115 0.288 0.04 0.6183 0.0006 0.0031 Phenylpropanoic Acids Phenyllactic acid HMDB0000779 C01479 0.2062 0.45106 1.336 0.7125 0.001 0.0076 2.147 1.738 0.2875 0.561 1.19 0.6793 0.01 0.0228 Organic Acids Maleic acid HMDB0000176 C01384 <0.001 0.017 -0.88 2.3177 0.0872 0.197 0.43 0.934 0.912 0.950 -0.05 0.0033 7E-06 <0.001 Organic Acids Pimelic acid HMDB0000857 C02656 0.207 0.45106 14.13 0.344 0.010 0.0353 17.53 1.073 0.1242 0.301 15.41 0.754 0.02 0.0499 SCFAs 2-Methylpentanoic acid HMDB0031580 - 0.075 0.264 0.36 0.889 <0.001 0.002 0.98 1.757 0.1099 0.288 0.31 1.0539 6E-06 <0.001 Organic Acids Pyruvic acid HMDB0000243 C00022 0.1881 0.43524 -0.48 0.2487 0.178 0.3249 -0.37 0.768 <0.001 <0.001 -1.57 2.3614 0.00 0.0015 Bile Acids TCDCA HMDB0000951 C05465 0.118 0.343 2.22 0.3909 <0.001 0.005 3.62 1.258 0.9092 0.950 0.45 0.0952 0.0004 0.0025 Organic Acids Oxoglutaric acid HMDB0000208 C00026 0.0442 0.20434 0.891 1.5354 <0.001 <0.001 0.879 1.487 0.3175 0.589 0.11 0.7912 0.00 0.0042 Bile Acids GCA HMDB0000138 C01921 0.770 0.842 0.17 0.2691 0.0209 0.065 1.56 0.728 0.7357 0.871 -0.16 0.5175 0.0162 0.0418 Fatty Acids Octanoic acid HMDB0000482 C06423 0.2786 0.53311 -0.17 0.5476 0.069 0.1592 2.131 1.02 0.0977 0.288 -0.25 1.2516 0.01 0.0278 Bile Acids CDCA HMDB0000518 C02528 0.004 0.064 -0.97 1.9874 0.0439 0.111 -1.33 0.75 0.5801 0.813 -0.20 0.0776 0.0098 0.0288 Bile Acids DCA HMDB0000626 C04483 0.0442 0.20434 -0.7 1.4687 0.013 0.045 -1.57 1.445 0.0081 0.060 -0.94 2.0178 0.01 0.0254 Fatty Acids Nonanoic acid HMDB0000847 C01601 0.705 0.792 0.10 0.3487 0.0228 0.067 0.77 1.153 0.8017 0.908 -0.07 0.4145 0.0049 0.0174 Fatty Acids Decanoic acid HMDB0000511 C01571 0.4379 0.63142 -0.31 0.5643 0.023 0.0666 3.266 1.14 0.2758 0.543 -0.57 0.0595 0.00 0.0174 Fatty Acids Undecylenic acid HMDB0033724 C13910 0.544 0.705 -0.13 0.0302 <0.001 0.003 -2.76 1.819 0.0032 0.029 -1.60 1.9347 0.0005 0.0031 Fatty Acids 5-Dodecenoic acid HMDB0000529 - 0.0442 0.20434 -0.98 1.0462 0.002 0.0114 -1.6 0.837 <0.001 0.011 -1.51 1.8089 0.01 0.0257 8,11,14-Eicosatrienoic Fatty Acids acid HMDB0002925 C03242 0.034 0.183 0.94 1.5072 0.0051 0.023 1.28 1.578 0.1815 0.410 0.53 0.7195 0.0141 0.0385 Carnitines Propionylcarnitine HMDB0000824 C03017 0.3696 0.59308 0.3 0.3817 0.006 0.0248 0.907 1.494 0.7572 0.886 -0.08 0.343 0.01 0.0175 Carnitines Malonylcarnitine HMDB0002095 - 0.192 0.439 -0.06 1.0785 0.0319 0.088 0.17 1.16 0.7739 0.890 -0.02 0.0695 0.0101 0.0291 Carnitines Butyrylcarnitine HMDB0002013 C02862 0.6109 0.73675 -0.04 0.5046 0.134 0.2606 0.463 0.842 0.0275 0.151 -0.30 0.6959 0.02 0.0416 2- Carnitines Methylbutyroylcarnitine HMDB0000378 - 0.024 0.156 -0.17 1.4797 0.347 0.497 0.02 0.027 0.1461 0.346 -0.16 1.2195 0.0031 0.0118 3- Hydroxylisovalerylcarni Carnitines tine - - 0.0756 0.26378 0.176 0.7897 <0.001 0.0019 0.624 1.551 0.0549 0.219 0.18 1.0826 0.00 0.0025 Carnitines Glutarylcarnitine HMDB0013130 - 0.007 0.077 -1.10 1.9659 0.2514 0.407 -0.35 0.618 0.4923 0.778 -0.47 0.4844 0.0102 0.0291 Carnitines Hexanylcarnitine HMDB0000705 - 0.0144 0.10987 -0.36 1.5109 0.260 0.4081 -0.22 0.255 <0.001 <0.001 -0.61 2.1799 0.00 0.0025 Carnitines Octanoylcarnitine HMDB0000791 C02838 <0.001 0.013 -1.19 1.8693 0.0156 0.051 -1.55 0.994 <0.001 0.001 -2.25 2.3595 0.0002 0.0019 Carnitines Decanoylcarnitine C10 HMDB0000651 - <0.001 0.01124 -1.04 1.929 0.011 0.0376 -1.31 1.309 <0.001 <0.001 -1.41 2.4164 0.00 0.0023 Carnitines Lauroylcarnitine HMDB0002250 - 0.056 0.232 -0.32 1.5984 <0.001 0.003 -1.73 1.583 <0.001 0.007 -2.31 2.0478 0.0012 0.0058 Carnitines Oleylcarnitine C18 1 HMDB0005065 - 0.441 0.63143 0.275 0.4818 0.009 0.0324 1.18 1.505 0.035 0.166 0.60 1.3856 0.01 0.0386 Carnitines Linoleylcarnitine HMDB0006469 - 0.184 0.430 -0.81 0.5237 0.0132 0.045 1.03 1.236 0.0588 0.225 0.67 0.8809 0.0024 0.0098 Bile Acids NorCA - - 0.0039 0.0642 0.011 1.2554 <0.001 0.0041 0.152 1.089 0.0229 0.130 0.00 0.5068 0.00 0.0086
Table S6. 11 mtabolites of urea cycle and TCA cycle presented marked difference across stages in the discovery cohort by targeted metabolomics analysis (related to figure 3) Normal VS Mild Normal VS Severe Normal VS Recovery Total Class Name HMDB_ID KEGG_ID P FDR log2FC VIP P FDR log2FC VIP P FDR log2FC VIP P FDR Amino Acids Proline HMDB0000162 C00148 0.035 0.183 -0.35 1.3856 0.7825 0.8547 -0.05 0.285 0.0527 0.2194 0.318 1.084 0.002 0.007 Amino Acids Creatine HMDB0000064 C00300 0.2917 0.5432 0.341 0.6911 0.0036 0.0165 1.969 1.569 0.2758 0.5435 -0.26 0.5015 0.0002 0.0019 Amino Acids Aspartic acid HMDB0000191 C00049 <0.001 0.002 1.403 2.4534 <0.001 0.0035 1.162 1.623 <0.001 <0.001 1.122 2.205 0.000 0.001 Amino Acids Arginine HMDB0000517 C00062 0.9143 0.94804 0.016 0.0469 0.0019 0.0113 -0.48 1.643 0.0089 0.0603 -0.37 1.3098 0.0025 0.00975 Amino Acids Ornithine HMDB0000214 C00077 0.031 0.182 0.371 1.5216 <0.001 0.0035 0.981 1.794 <0.001 <0.001 1.557 2.314 0.000 <0.001 Amino Acids Glutamine HMDB0000641 C00064 0.0373 0.18541 -0.36 1.4032 0.0019 0.0113 -0.62 1.791 0.0043 0.0346 -0.48 1.8552 0.0019 0.00817 Amino Acids Citrulline HMDB0000904 C00327 0.007 0.077 -0.59 1.7025 0.0233 0.0672 -0.49 1.342 0.2564 0.5316 -0.28 0.381 0.026 0.061 Organic Acids Pyruvic acid HMDB0000243 C00022 0.1881 0.43524 -0.48 0.2487 0.1783 0.3249 -0.37 0.768 <0.001 <0.001 -1.57 2.3614 0.0002 0.00146 Organic Acids Malic acid HMDB0000156 C00149 0.426 0.631 0.163 0.3095 <0.001 0.0037 0.711 1.387 <0.001 0.0066 0.765 1.630 0.000 0.00102 Organic Acids Oxoglutaric acid HMDB0000208 C00026 0.0442 0.20434 0.891 1.5354 <0.001 <0.001 0.879 1.487 0.3175 0.5891 0.106 0.7912 0.0008 0.00425 Organic Acids Fumaric acid HMDB0000134 C00122 0.011 0.098 -0.77 1.9912 0.171 0.3151 0.461 0.744 0.55 0.8109 0.149 0.131 0.000 0.00246
Table S7. 11 mtabolites in table S6 verified with marked difference across stages in the validation cohort by targeted metabolomics analysis (related to figure 3) Normal VS Mild Normal VS Severe Normal VS Recovery Total Class Name HMDB_ID KEGG_ID P FDR log2FC VIP P FDR log2FC VIP P FDR log2FC VIP P FDR Amino Acids Proline HMDB0000162 C00148 0.723 0.88364 -0.04 0.1954 0.7449 0.7449 -0.05 0.28 0.508 0.6985 0.087 0.387 0.674 0.674 Amino Acids Creatine HMDB0000064 C00300 1 1 0.055 0.74 0.0179 0.0543 0.621 0.8 0.1413 0.3108 -0.47 1.1978 0.0011 0.0039 Amino Acids Aspartic acid HMDB0000191 C00049 0.000 0.00075 0.552 1.9226 0.0046 0.0256 0.602 1.198 0.0008 0.0086 0.487 1.673 0.0005 0.0027 Amino Acids Arginine HMDB0000517 C00062 0.5058 0.88364 -0.11 0.2043 0.0221 0.0543 -0.38 0.659 0.8748 0.8748 0.021 0.0217 0.1035 0.1423 Amino Acids Ornithine HMDB0000214 C00077 0.978 1 -0.2 0.2909 0.0582 0.08 0.408 0.829 0.2403 0.4406 0.318 0.8414 0.215 0.263 Amino Acids Glutamine HMDB0000641 C00064 0.056 0.15388 -0.21 1.3017 0.0247 0.0543 -0.32 1.508 0.0491 0.1799 -0.22 1.3212 0.0771 0.1212 Amino Acids Citrulline HMDB0000904 C00327 0.0098 0.03592 -0.28 2.0044 0.046 0.0723 -0.36 0.923 0.0793 0.218 -0.28 1.0479 0.0734 0.1212 Organic Acids Pyruvic acid HMDB0000243 C00022 0.6381 0.88364 -0.14 0.2986 0.0721 0.0881 -0.72 0.98 0.0017 0.0095 -0.93 1.6329 0.0044 0.0121 Organic Acids Malic acid HMDB0000156 C00149 0.7172 0.88364 -0.27 0.1704 0.0315 0.0578 0.398 0.753 0.5817 0.711 0.045 0.4834 0.0707 0.1212 Organic Acids Oxoglutaric acid HMDB0000208 C00026 0.0015 0.00817 0.787 0.8295 <0.001 0.0009 1.013 1.598 0.428 0.6726 -0.28 0.3292 <0.001 <0.001 Organic Acids Fumaric acid HMDB0000134 C00122 0.42 0.88364 -0.48 0.2704 0.2221 0.2443 0.116 0.72 0.6796 0.7476 -0.05 0.2367 0.2749 0.3024