Summary of Study ST003177
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001976. The data can be accessed directly via it's Project DOI: 10.21228/M89J06 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
Study ID | ST003177 |
Study Title | A Longitudinal Study in Rheumatoid Arthritis Unveils Metabolomic Biomarkers Preceding Clinical Onset, Assessing Disease Severity, and Anticipating Treatment Response to csDMARDs |
Study Summary | Rheumatoid arthritis (RA) is a bundle of systemic inflammatory diseases mainly affecting the joints, complicating the identification of biomarkers for early diagnosis, predicting disease progress and therapeutic outcomes. This study scrutinizes a longitudinal cohort of RA, inclusive of follow-ups, alongside OA, UA and ACPA/RF-RA and healthy controls, aiming to discover plasma metabolic markers that can precede RA onset, assess disease activity, and forecast treatment efficacy. Our investigation revealed substantial metabolic alterations at both the pathway and individual metabolite levels across RA, at-risk or RA and healthy control. The drug response predictive models constructed on critical differential metaboites showed optimal performance. Additionally, our longitudinal data sheds light on the molecular impacts on metabolism of csDMARDs in RA. |
Institute | West China Hospital of Sichuan University |
Last Name | Zhu |
First Name | Chenxi |
Address | West China Hospital, Sichuan University, 37# Guoxue Xiang, Chengdu, Sichuan, 610041, China. |
chenxizhu1995@gmail.com | |
Phone | +8615026603760 |
Submit Date | 2024-04-12 |
Raw Data Available | Yes |
Raw Data File Type(s) | mzML |
Analysis Type Detail | LC-MS |
Release Date | 2024-05-11 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR001976 |
Project DOI: | doi: 10.21228/M89J06 |
Project Title: | A Longitudinal Study in Rheumatoid Arthritis Unveils Metabolomic Biomarkers Preceding Clinical Onset, Assessing Disease Severity, and Anticipating Treatment Response to csDMARDs |
Project Summary: | Rheumatoid arthritis (RA) is a bundle of systemic inflammatory diseases mainly affecting the joints, complicating the identification of biomarkers for early diagnosis, predicting disease progress and therapeutic outcomes. This study scrutinizes a longitudinal cohort of RA, inclusive of follow-ups, alongside OA, UA and ACPA/RF-RA and healthy controls, aiming to discover plasma metabolic markers that can precede RA onset, assess disease activity, and forecast treatment efficacy. Our investigation revealed substantial metabolic alterations at both the pathway and individual metabolite levels across RA, at-risk or RA and healthy control. The drug response predictive models constructed on critical differential metaboites showed optimal performance. Additionally, our longitudinal data sheds light on the molecular impacts on metabolism of csDMARDs in RA. |
Institute: | Department of Rheumatology and Immunology, West China Hospital,Sichuan University, Chengdu, Sichuan, China |
Last Name: | Zhu |
First Name: | Chenxi |
Address: | West China Hospital, Sichuan University, 37# Guoxue Xiang, Chengdu, Sichuan, 610041, China., Chengdu, Sichuan, 610065, China |
Email: | chenxizhu1995@gmail.com |
Phone: | +86 150 2660 3760 |
Subject:
Subject ID: | SU003296 |
Subject Type: | Human |
Subject Species: | Homo sapiens |
Taxonomy ID: | 9606 |
Species Group: | Mammals |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
mb_sample_id | local_sample_id | Clinical group | Sample source |
---|---|---|---|
SA343818 | NEG_140 | CCP-RA | blood |
SA343819 | POS_475 | CCP-RA | blood |
SA343820 | NEG_226 | CCP-RA | blood |
SA343821 | NEG_560 | CCP-RA | blood |
SA343822 | POS_637 | CCP-RA | blood |
SA343823 | POS_226 | CCP-RA | blood |
SA343824 | POS_987 | CCP-RA | blood |
SA343825 | POS_140 | CCP-RA | blood |
SA343826 | POS_472 | CCP-RA | blood |
SA343827 | NEG_475 | CCP-RA | blood |
SA343828 | NEG_464 | CCP-RA | blood |
SA343829 | NEG_461 | CCP-RA | blood |
SA343830 | POS_980 | CCP-RA | blood |
SA343831 | POS_310 | CCP-RA | blood |
SA343832 | POS_560 | CCP-RA | blood |
SA343833 | NEG_980 | CCP-RA | blood |
SA343834 | NEG_472 | CCP-RA | blood |
SA343835 | NEG_987 | CCP-RA | blood |
SA343836 | POS_464 | CCP-RA | blood |
SA343837 | NEG_310 | CCP-RA | blood |
SA343838 | POS_461 | CCP-RA | blood |
SA343839 | NEG_637 | CCP-RA | blood |
SA345220 | NEG_942 | health | blood |
SA345221 | POS_113 | health | blood |
SA345222 | POS_624 | health | blood |
SA345223 | POS_17 | health | blood |
SA345224 | POS_109 | health | blood |
SA345225 | POS_281 | health | blood |
SA345226 | POS_942 | health | blood |
SA345227 | POS_279 | health | blood |
SA345228 | POS_915 | health | blood |
SA345229 | NEG_965 | health | blood |
SA345230 | POS_923 | health | blood |
SA345231 | POS_947 | health | blood |
SA345232 | POS_931 | health | blood |
SA345233 | POS_11 | health | blood |
SA345234 | POS_619 | health | blood |
SA345235 | NEG_958 | health | blood |
SA345236 | POS_611 | health | blood |
SA345237 | POS_605 | health | blood |
SA345238 | NEG_961 | health | blood |
SA345239 | NEG_947 | health | blood |
SA345240 | POS_548 | health | blood |
SA345241 | POS_991 | health | blood |
SA345242 | POS_621 | health | blood |
SA345243 | POS_926 | health | blood |
SA345244 | POS_550 | health | blood |
SA345245 | POS_733 | health | blood |
SA345246 | POS_111 | health | blood |
SA345247 | NEG_977 | health | blood |
SA345248 | POS_976 | health | blood |
SA345249 | POS_540 | health | blood |
SA345250 | POS_975 | health | blood |
SA345251 | POS_974 | health | blood |
SA345252 | POS_973 | health | blood |
SA345253 | POS_977 | health | blood |
SA345254 | NEG_902 | health | blood |
SA345255 | POS_105 | health | blood |
SA345256 | POS_719 | health | blood |
SA345257 | POS_541 | health | blood |
SA345258 | NEG_11 | health | blood |
SA345259 | POS_288 | health | blood |
SA345260 | POS_726 | health | blood |
SA345261 | POS_972 | health | blood |
SA345262 | POS_724 | health | blood |
SA345263 | POS_965 | health | blood |
SA345264 | POS_722 | health | blood |
SA345265 | POS_580 | health | blood |
SA345266 | NEG_33 | health | blood |
SA345267 | POS_967 | health | blood |
SA345268 | POS_577 | health | blood |
SA345269 | NEG_17 | health | blood |
SA345270 | POS_971 | health | blood |
SA345271 | POS_970 | health | blood |
SA345272 | POS_720 | health | blood |
SA345273 | NEG_26 | health | blood |
SA345274 | POS_542 | health | blood |
SA345275 | POS_728 | health | blood |
SA345276 | NEG_974 | health | blood |
SA345277 | NEG_973 | health | blood |
SA345278 | NEG_975 | health | blood |
SA345279 | NEG_976 | health | blood |
SA345280 | NEG_926 | health | blood |
SA345281 | NEG_931 | health | blood |
SA345282 | NEG_972 | health | blood |
SA345283 | NEG_967 | health | blood |
SA345284 | POS_545 | health | blood |
SA345285 | NEG_970 | health | blood |
SA345286 | NEG_971 | health | blood |
SA345287 | POS_732 | health | blood |
SA345288 | POS_629 | health | blood |
SA345289 | NEG_923 | health | blood |
SA345290 | POS_285 | health | blood |
SA345291 | POS_543 | health | blood |
SA345292 | NEG_991 | health | blood |
SA345293 | POS_982 | health | blood |
SA345294 | POS_981 | health | blood |
SA345295 | NEG_915 | health | blood |
SA345296 | POS_983 | health | blood |
SA345297 | NEG_982 | health | blood |
Collection:
Collection ID: | CO003289 |
Collection Summary: | The study collected plasma samples from all participants at West China Hospital, Sichuan University. These were approved by the Research Ethics Committee of West China Hospital, Sichuan University (Permission number: 2021(790)), and informed consent was obtained from all participants. Patients were diagnosed with RA according to the 2010 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) criteria. The healthy control group consisted of individuals matched in age and gender, with no history or clinical evidence of autoimmune or rheumatic diseases. Blood collection followed standard venipuncture procedures using anticoagulant tubes. Plasma samples were obtained after centrifugation and stored at -80°C. ACPA levels were measured using Elecsys anti-CCP detection on the Cobas® e 801 module (Roche Diagnostics, Mannheim, Germany), with results categorized as positive (≥17.0 U/ml) or negative (<17.0 U/ml). |
Sample Type: | Blood (plasma) |
Treatment:
Treatment ID: | TR003305 |
Treatment Summary: | A subset of RA patients were followed-up for three months after treatment with MTX monotherapy or a combination of csDMARDs. During this period, clinical data and blood specimens were gathered at the conclusion. |
Sample Preparation:
Sampleprep ID: | SP003303 |
Sampleprep Summary: | The plasma samples were thawed by transferring them from -80°C to a 4°C refrigerator. Then, take out 50 μL of the plasma sample into another tube after vortex mixing and added to 250 μL of pre-cooled Spike MeOH containing isotopic chemicals (120.89 μM 13C6-D-glucose, 23.12 mM 13C5-L-glutamate-15N). The mixture was thoroughly mixed by vortexing at 1500 rpm for 2 minutes at 4°C. The mixture was then placed in a -20°C refrigerator and allowed to stand for 30 minutes. Afterward, ultrasonication was performed in an ice-water bath for 10 minutes. Following ultrasonication, the mixture was centrifuged at 13,000 rpm for 20 minutes at 4°C. 20 μL of each sample from every batch was extracted from the tube and mixed for QC analysis using mass spectrometry (MS). The 150ul remaining extract was concentrated, vacuum dried, and stored at -80°C. |
Combined analysis:
Analysis ID | AN005215 | AN005216 |
---|---|---|
Analysis type | MS | MS |
Chromatography type | HILIC | HILIC |
Chromatography system | SCIEX ExionLC UHPLC | SCIEX ExionLC UHPLC |
Column | Waters ACQUITY UPLC BEH Amide (100 x 2.1mm,1.7um) | Waters ACQUITY UPLC BEH Amide (100 x 2.1mm,1.7um) |
MS Type | ESI | ESI |
MS instrument type | Triple quadrupole | Triple quadrupole |
MS instrument name | ABI Sciex Triple Quad 5500+ | ABI Sciex Triple Quad 5500+ |
Ion Mode | POSITIVE | NEGATIVE |
Units | peak area | Peak area |
Chromatography:
Chromatography ID: | CH003944 |
Chromatography Summary: | SCIEX ExionLC UHPLC system coupled with a SCIEX Triple Quad 5500+ LC-MS/MS |
Instrument Name: | SCIEX ExionLC UHPLC |
Column Name: | Waters ACQUITY UPLC BEH Amide (100 x 2.1mm,1.7um) |
Column Temperature: | 40°C |
Flow Gradient: | 1.5 min, 90% B; 5 min, 45% B; 10 min, 45% B; 12 min, 90% B; 25 min, 90% B |
Flow Rate: | 0.3 mL/min |
Solvent A: | 90% water/10% acetonitrile; 10 mM ammonium acetate; 0.2% acetic acid |
Solvent B: | 90% acetonitrile/10% water; 10 mM ammonium acetate; 0.2% acetic acid |
Chromatography Type: | HILIC |
MS:
MS ID: | MS004948 |
Analysis ID: | AN005215 |
Instrument Name: | ABI Sciex Triple Quad 5500+ |
Instrument Type: | Triple quadrupole |
MS Type: | ESI |
MS Comments: | Within each batch, normalization was performed by dividing the level of each metabolite by the average value of the first and last QC samples in that batch. Subsequently, a cross-sample total sum correction was conducted for all metabolites. Then, the data was mean-centered and divided by the standard deviation of each variable for standardization. Finally, a log10 transformation was applied to the data. We further removed metabolites with a coefficient of variation (CV) greater than 0.35 and any metabolites with more than 50% missing values within any group (RA, at-risk of RA, and Health). For analyses intolerant to missing data, any missing values are substituted with 1/5 of the minimum positive value of their corresponding variables. |
Ion Mode: | POSITIVE |
MS ID: | MS004949 |
Analysis ID: | AN005216 |
Instrument Name: | ABI Sciex Triple Quad 5500+ |
Instrument Type: | Triple quadrupole |
MS Type: | ESI |
MS Comments: | Within each batch, normalization was performed by dividing the level of each metabolite by the average value of the first and last QC samples in that batch. Subsequently, a cross-sample total sum correction was conducted for all metabolites. Then, the data was mean-centered and divided by the standard deviation of each variable for standardization. Finally, a log10 transformation was applied to the data. We further removed metabolites with a coefficient of variation (CV) greater than 0.35 and any metabolites with more than 50% missing values within any group (RA, at-risk of RA, and Health). For analyses intolerant to missing data, any missing values are substituted with 1/5 of the minimum positive value of their corresponding variables. |
Ion Mode: | NEGATIVE |