Summary of Study ST002302

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 PR001475. The data can be accessed directly via it's Project DOI: 10.21228/M82M60 This work is supported by NIH grant, U2C- DK119886.

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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.

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Study IDST002302
Study TitleIntegrated metabolomics and lipidomics study of patients with atopic dermatitis in response to dupilumab
Study SummaryBackground: Atopic dermatitis (AD) is one of the most common chronic inflammatory skin diseases. Dupilumab, a monoclonal antibody that targets the interleukin (IL)-4 and IL-13 receptors, has been widely used in AD because of its efficacy. However, metabolic changes occurring in patients with AD in response to dupilumab remains unknown. In this study, we integrated metabolomics and lipidomics analyses with clinical data to explore potential metabolic alterations associated with dupilumab therapeutic efficacy. In addition, we investigate whether the development of treatment side effects was linked to the dysregulation of metabolic pathways. Methods: A total of 33 patients with AD were included in the current study, with serum samples collected before and after treatment with dupilumab. Comprehensive metabolomic and lipidomic analyses have previously been developed to identify serum metabolites (including lipids) that vary among treatment groups. An orthogonal partial least squares discriminant analysis model was established to screen for differential metabolites and metabolites with variable importance in projection > 1 and p < 0.05 were considered potential metabolic biomarkers. MetaboAnalyst 5.0 was used to identify related metabolic pathways. Patients were further classified into two groups, well responders (n = 19) and poor responders (n = 14), to identify differential metabolites between the two groups. Results: The results revealed significant changes in serum metabolites before and after 16 weeks of dupilumab treatment. Variations in the metabolic profile were more significant in the well-responder group than in the poor-responder group. Pathway enrichment analysis revealed that differential metabolites derived from the well-responder group were mainly involved in glycerophospholipid metabolism, valine, leucine and isoleucine biosynthesis, the citrate cycle, arachidonic acid metabolism, pyrimidine metabolism, and sphingolipid metabolism. Conclusion: Serum metabolic profiles of patients with AD varied significantly after treatment with dupilumab. Differential metabolites and their related metabolic pathways may provide clues for understanding the effects of dupilumab on patient metabolism.
Institute
Peking Union Medical College Hospital, Chinese Academy of Medical Sciences
Last NameZhang
First NameLishan
AddressNo.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
Email429647356@qq.com
Phone+86-18612636397
Submit Date2022-10-01
Raw Data AvailableYes
Raw Data File Type(s)mzXML
Analysis Type DetailGC-MS/LC-MS
Release Date2022-10-18
Release Version1
Lishan Zhang Lishan Zhang
https://dx.doi.org/10.21228/M82M60
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001475
Project DOI:doi: 10.21228/M82M60
Project Title:Integrated metabolomics and lipidomics study of patients with atopic dermatitis in response to dupilumab
Project Summary:Background: Atopic dermatitis (AD) is one of the most common chronic inflammatory skin diseases. Dupilumab, a monoclonal antibody that targets the interleukin (IL)-4 and IL-13 receptors, has been widely used in AD because of its efficacy. However, metabolic changes occurring in patients with AD in response to dupilumab remains unknown. In this study, we integrated metabolomics and lipidomics analyses with clinical data to explore potential metabolic alterations associated with dupilumab therapeutic efficacy. In addition, we investigate whether the development of treatment side effects was linked to the dysregulation of metabolic pathways. Methods: A total of 33 patients with AD were included in the current study, with serum samples collected before and after treatment with dupilumab. Comprehensive metabolomic and lipidomic analyses have previously been developed to identify serum metabolites (including lipids) that vary among treatment groups. An orthogonal partial least squares discriminant analysis model was established to screen for differential metabolites and metabolites with variable importance in projection > 1 and p < 0.05 were considered potential metabolic biomarkers. MetaboAnalyst 5.0 was used to identify related metabolic pathways. Patients were further classified into two groups, well responders (n = 19) and poor responders (n = 14), to identify differential metabolites between the two groups. Results: The results revealed significant changes in serum metabolites before and after 16 weeks of dupilumab treatment. Variations in the metabolic profile were more significant in the well-responder group than in the poor-responder group. Pathway enrichment analysis revealed that differential metabolites derived from the well-responder group were mainly involved in glycerophospholipid metabolism, valine, leucine and isoleucine biosynthesis, the citrate cycle, arachidonic acid metabolism, pyrimidine metabolism, and sphingolipid metabolism. Conclusion: Serum metabolic profiles of patients with AD varied significantly after treatment with dupilumab. Differential metabolites and their related metabolic pathways may provide clues for understanding the effects of dupilumab on patient metabolism.
Institute:Peking Union Medical College Hospital, Chinese Academy of Medical Sciences
Last Name:Zhang
First Name:Lishan
Address:No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
Email:429647356@qq.com
Phone:+86-18612636397

Subject:

Subject ID:SU002388
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Age Or Age Range:>=18
Gender:Male and female
Human Race:Chinese
Human Ethnicity:Han
Human Trial Type:observational study
Human Medications:Dupilumab
Human Inclusion Criteria:1.Age ≥ 18 years of age 2.Dermatologist diagnosis of moderate to severe AD, EASI≥16 at baseline 3.Eligible to receive dupilumab therapy for AD in accordance with the guidelines. Patients who are eligible were treated with a fixed schedule of 300mg dupilumab in 2-week intervals. Patients who did not achieve 16-week therapy were excluded. 4.During the whole treatment process, the requirements for diet and exercise are roughly the same as before treatment, so as to keep the body healthy and balanced 5.A 30-day washout period of systemic medications preceded treatment
Human Exclusion Criteria:1Evidence of other skin diseases except for AD at baseline 2.Pregnancy or breast feeding, 3.Patients with permanent severe diseases, especially those affecting the immune system, except asthma 4.Patients with severe mental illness 5.Evidence of chronic metabolic disease, including Obesity, diabetes, fatty liver, osteoporosis, atherosclerotic cardiovascular and cerebrovascular diseases, and metabolic-related cancers (breast, colorectal, pancreatic, colon, and prostate cancer). 6.Application of other systemic medications during treatment

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id Treatment
SA226584B11After dupilumab treatment
SA226585B10After dupilumab treatment
SA226586B9After dupilumab treatment
SA226587B12After dupilumab treatment
SA226588B13After dupilumab treatment
SA226589B15After dupilumab treatment
SA226590B14After dupilumab treatment
SA226591B8After dupilumab treatment
SA226592B7After dupilumab treatment
SA226593B2After dupilumab treatment
SA226594B1After dupilumab treatment
SA226595B3After dupilumab treatment
SA226596B4After dupilumab treatment
SA226597B6After dupilumab treatment
SA226598B5After dupilumab treatment
SA226599B16After dupilumab treatment
SA226600B17After dupilumab treatment
SA226601B29After dupilumab treatment
SA226602B28After dupilumab treatment
SA226603B27After dupilumab treatment
SA226604B30After dupilumab treatment
SA226605B31After dupilumab treatment
SA226606B33After dupilumab treatment
SA226607B32After dupilumab treatment
SA226608B25After dupilumab treatment
SA226609B26After dupilumab treatment
SA226610B19After dupilumab treatment
SA226611B18After dupilumab treatment
SA226612B20After dupilumab treatment
SA226613B21After dupilumab treatment
SA226614B24After dupilumab treatment
SA226615B23After dupilumab treatment
SA226616B22After dupilumab treatment
SA226617A32Before dupilumab treatment
SA226618A33Before dupilumab treatment
SA226619A31Before dupilumab treatment
SA226620A30Before dupilumab treatment
SA226621A9Before dupilumab treatment
SA226622A8Before dupilumab treatment
SA226623A10Before dupilumab treatment
SA226624A11Before dupilumab treatment
SA226625A14Before dupilumab treatment
SA226626A12Before dupilumab treatment
SA226627A7Before dupilumab treatment
SA226628A6Before dupilumab treatment
SA226629A2Before dupilumab treatment
SA226630A1Before dupilumab treatment
SA226631A3Before dupilumab treatment
SA226632A4Before dupilumab treatment
SA226633A5Before dupilumab treatment
SA226634A15Before dupilumab treatment
SA226635A13Before dupilumab treatment
SA226636A16Before dupilumab treatment
SA226637A24Before dupilumab treatment
SA226638A26Before dupilumab treatment
SA226639A27Before dupilumab treatment
SA226640A29Before dupilumab treatment
SA226641A28Before dupilumab treatment
SA226642A23Before dupilumab treatment
SA226643A25Before dupilumab treatment
SA226644A18Before dupilumab treatment
SA226645A22Before dupilumab treatment
SA226646A19Before dupilumab treatment
SA226647A17Before dupilumab treatment
SA226648A20Before dupilumab treatment
SA226649A21Before dupilumab treatment
SA226650QC02Control
SA226651QC03Control
SA226652QC04Control
SA226653QC06Control
SA226654QC01Control
SA226655QC07Control
SA226656QC05Control
Showing results 1 to 73 of 73

Collection:

Collection ID:CO002381
Collection Summary:We recruited 33 patients diagnosed with moderate to severe atopic dermatitis at the dermatology outpatient clinic of the Peking Union Medical College Hospital from March 2021 to February 2022. Serum samples from each participant were obtained after overnight fasting at the outpatient clinic of the Peking Union Medical College Hospital and were collected before and after 16 weeks of dupilumab treatment. The serum samples were immediately frozen at -80°C until analysis.
Sample Type:Blood (serum)
Storage Conditions:-80℃

Treatment:

Treatment ID:TR002400
Treatment Summary:All the enrolled participants were treated with dupilumab for 16 weeks.
Treatment:Biologics Formulation
Treatment Route:in 2-week intervals
Treatment Dose:300mg dupilumab
Treatment Dosevolume:300mg dupilumab

Sample Preparation:

Sampleprep ID:SP002394
Sampleprep Summary:Metabolomics_LC-MS 100 μL of sample was transferred to an EP tube. After the addition of 400 μL of extract solution (acetonitrile: methanol = 1: 1, containing isotopically-labelled internal standard mixture), the samples were vortexed for 30 s, sonicated for 10 min in ice-water bath, and incubated for 1 h at -40 ℃ to precipitate proteins. Then the sample was centrifuged at 12000 rpm(RCF=13800(×g),R= 8.6cm) for 15 min at 4 ℃. The resulting supernatant was transferred to a fresh glass vial for analysis. The quality control (QC) sample was prepared by mixing an equal aliquot of the supernatants from all of the samples. Metabolomics_GC-MS Transfer 50 μL sample to EP tube and add 205 μL precooled extract methanol，(including internal L-2-Chlorophenylalanine, 1mg/mL stock), vortex mixing for 30 s. Ultrasound for 10 min (ice bath) . After centrifugation at 4 ℃ for 15 min at 12000 rpm(RCF=13800(×g),R= 8.6cm) . Carefully transfer the 180μL supernatant into a 1.5 mL EP tube. Take 50 μL of each sample and mix them into QC samples. Dry extract in vacuum concentrator. After evaporation in a vacuum concentrator, 30 μL of Methoxyamination hydrochloride (20 mg/mL in pyridine) was added and then incubated at 80 ℃ for 30 min, then derivatized by 40 μL of BSTFA regent (1% TMCS, v/v) at 70 ℃ for 1.5h. Gradually cooling samples to room temperature, 5 μL of FAMEs (in chloroform) was added to QC sample. All samples were then analyzed by gas chromatograph coupled with a time-of-flight mass spectrometer (GC-TOF-MS). Lipidomics 100 μL of sample was transferred to an EP tube, and added with 480 μL of extract solution (MTBE: methanol1 = 5: 1). After 30 s vortex, the samples were sonicated for 10min in ice-water bath, incubated at -40 ℃ for 1 h, and centrifuged at 3000 rpm (RCF=900(×g),R= 8.6cm) for 15 min at 4 ℃. r l.a$quchu1` μL of supernatant was transferred to a fresh tube and dried in a vacuum concentrator at 37 ℃. Then, the dried samples were reconstituted in 100 μL of 50% methanol in dichloromethane. After 30s vortex, the samples were sonicated for 10 min in ice-water bath. The constitution was then centrifuged at 13000 rpm (RCF=16200(×g),R= 8.6cm) for 15 min at 4 ℃, and 75 μL of supernatant was transferred to a fresh glass vial for LC/MS analysis. The quality control (QC) sample was prepared by mixing an equal aliquot 20 μL of the supernatants from all of the samples.

Combined analysis:

Analysis ID AN003758 AN003759 AN003760 AN003761 AN003762
Analysis type MS MS MS MS MS
Chromatography type GC HILIC HILIC HILIC HILIC
Chromatography system Agilent 7890N Thermo Vanquish Thermo Vanquish Thermo Vanquish Thermo Vanquish
Column Agilent DB5-MS (30m x 0.25mm, 0.25um) Waters Acquity BEH C8 (100 x 2.1mm,1.7um) Waters Acquity BEH C8 (100 x 2.1mm,1.7um) Waters Acquity BEH C8 (100 x 2.1mm,1.7um) Waters Acquity BEH C8 (100 x 2.1mm,1.7um)
MS Type EI ESI ESI ESI ESI
MS instrument type GC-TOF Orbitrap Orbitrap Orbitrap Orbitrap
MS instrument name Agilent 7890A Thermo Q Exactive HF-X Orbitrap Thermo Q Exactive HF-X Orbitrap Thermo Q Exactive HF-X Orbitrap Thermo Q Exactive HF-X Orbitrap
Ion Mode UNSPECIFIED POSITIVE NEGATIVE POSITIVE NEGATIVE
Units Peak area Peak area Peak area Peak area Peak area

Chromatography:

Chromatography ID:CH002781
Instrument Name:Agilent 7890N
Column Name:Agilent DB5-MS (30m x 0.25mm, 0.25um)
Chromatography Type:GC
  
Chromatography ID:CH002782
Instrument Name:Thermo Vanquish
Column Name:Waters Acquity BEH C8 (100 x 2.1mm,1.7um)
Chromatography Type:HILIC

MS:

MS ID:MS003501
Analysis ID:AN003758
Instrument Name:Agilent 7890A
Instrument Type:GC-TOF
MS Type:EI
MS Comments:-
Ion Mode:UNSPECIFIED
  
MS ID:MS003502
Analysis ID:AN003759
Instrument Name:Thermo Q Exactive HF-X Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:-
Ion Mode:POSITIVE
  
MS ID:MS003503
Analysis ID:AN003760
Instrument Name:Thermo Q Exactive HF-X Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:-
Ion Mode:NEGATIVE
  
MS ID:MS003504
Analysis ID:AN003761
Instrument Name:Thermo Q Exactive HF-X Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:-
Ion Mode:POSITIVE
  
MS ID:MS003505
Analysis ID:AN003762
Instrument Name:Thermo Q Exactive HF-X Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:-
Ion Mode:NEGATIVE
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