#METABOLOMICS WORKBENCH Mahamogren_20231103_075033 DATATRACK_ID:4439 STUDY_ID:ST003056 ANALYSIS_ID:AN005010 VERSION 1 CREATED_ON 01-29-2024 #PROJECT #STUDY #SUBJECT #SUBJECT_SAMPLE_FACTORS: SUBJECT(optional)[tab]SAMPLE[tab]FACTORS(NAME:VALUE pairs separated by |)[tab]Additional sample data #COLLECTION #TREATMENT #SAMPLEPREP #CHROMATOGRAPHY #ANALYSIS #END #METABOLOMICS WORKBENCH Mahamogren_20231103_075033 DATATRACK_ID:4439 STUDY_ID:ST003056 ANALYSIS_ID:AN005010 VERSION 1 CREATED_ON 01-29-2024 #PROJECT PR:PROJECT_TITLE Untargeted metabolomics revealed multiple metabolic perturbations in plasma of PR:PROJECT_TITLE T2D patients in response to Liraglutide PR:PROJECT_SUMMARY Despite the global efforts put into the clinical research and studies in order PR:PROJECT_SUMMARY to protect against Type-2 diabetes mellitus (T2DM), the incidence of T2DM PR:PROJECT_SUMMARY remains high causing a major health problem and impacting the health and care PR:PROJECT_SUMMARY systems. Therefore, T2DM-related treatments and therapies are continuously PR:PROJECT_SUMMARY invented for the clinical use, including Liraglutide. The last is a GLP-1 PR:PROJECT_SUMMARY analogue and shows its beneficial health outcomes e.g., improved glycemic PR:PROJECT_SUMMARY control, lower body weight, and reduced cardiovascular disease risks. The PR:PROJECT_SUMMARY intrinsic mechanisms of these beneficial effects are not fully understood; PR:PROJECT_SUMMARY however, our research group has previously published proteomics work PR:PROJECT_SUMMARY demonstrating the involvement of certain important proteins in part in the PR:PROJECT_SUMMARY beneficial health outcomes of Liraglutide. Since proteomics and metabolomics are PR:PROJECT_SUMMARY complementary to each other in the context of the biological pathways, studying PR:PROJECT_SUMMARY the metabolic impacts of Liraglutide on T2DM patients would add further PR:PROJECT_SUMMARY information about the beneficial health outcomes of Liraglutide. Thus, herein, PR:PROJECT_SUMMARY we performed an untargeted metabolomics approach for identifying metabolic PR:PROJECT_SUMMARY pathways impacted by the treatment of Liraglutide in T2DM patients. Methods: PR:PROJECT_SUMMARY Untargeted liquid chromatography coupled with mass spectrometry was used for PR:PROJECT_SUMMARY metabolomics analysis of plasma samples collected from T2DM patients (n=20) PR:PROJECT_SUMMARY before and after receiving Liraglutide treatment. Metabolic profiling and PR:PROJECT_SUMMARY related pathway and network analyses were conducted. Results: The metabolic PR:PROJECT_SUMMARY profiling analyses identified 93 endogenous metabolites were significantly PR:PROJECT_SUMMARY affected by the Liraglutide treatments, which 49 metabolites up-regulated and 44 PR:PROJECT_SUMMARY metabolites down-regulated. Moreover, the metabolic pathway analyses revealed PR:PROJECT_SUMMARY that the most pronounced metabolite and metabolic pathways that were affected by PR:PROJECT_SUMMARY the Liraglutide treatment was Pentose and glucuronate interconversion, PR:PROJECT_SUMMARY suggesting the last may be a potential target of the Liraglutide treatment could PR:PROJECT_SUMMARY be involved in part in the beneficial effects seen in T2DM patients, specially, PR:PROJECT_SUMMARY we found that glucuronate interconversion pathway which is known by its role in PR:PROJECT_SUMMARY eliminating toxic and undesirable substances from the human body, impacted in PR:PROJECT_SUMMARY Liraglutide treated patients. The last findings ar consistence with our previous PR:PROJECT_SUMMARY proteomics findings. Conclusion: These findings, taken together with our PR:PROJECT_SUMMARY previous results, provide a deeper understanding of the underlying mechanisms PR:PROJECT_SUMMARY involved in the beneficial effects of Liraglutide at the proteomic and metabolic PR:PROJECT_SUMMARY levels in T2DM patients. PR:INSTITUTE King Faisal Specialist Hospital and Research Centre (KFSHRC) PR:LAST_NAME Al Mogren PR:FIRST_NAME Maha PR:ADDRESS Zahrawi Street, Al Maather, Riyadh 11211, Saudi Arabia PR:EMAIL malmogren@alfaisal.edu PR:PHONE 966541205332 PR:DOI http://dx.doi.org/10.21228/M83B08 #STUDY ST:STUDY_TITLE Untargeted metabolomics revealed multiple metabolic perturbations in plasma of ST:STUDY_TITLE T2D patients in response to Liraglutide - Part 2 ST:STUDY_SUMMARY Despite the global efforts put into the clinical research and studies in order ST:STUDY_SUMMARY to protect against Type-2 diabetes mellitus (T2DM), the incidence of T2DM ST:STUDY_SUMMARY remains high causing a major health problem and impacting the health and care ST:STUDY_SUMMARY systems. Therefore, T2DM-related treatments and therapies are continuously ST:STUDY_SUMMARY invented for the clinical use, including Liraglutide. The last is a GLP-1 ST:STUDY_SUMMARY analogue and shows its beneficial health outcomes e.g., improved glycemic ST:STUDY_SUMMARY control, lower body weight, and reduced cardiovascular disease risks. The ST:STUDY_SUMMARY intrinsic mechanisms of these beneficial effects are not fully understood; ST:STUDY_SUMMARY however, our research group has previously published proteomics work ST:STUDY_SUMMARY demonstrating the involvement of certain important proteins in part in the ST:STUDY_SUMMARY beneficial health outcomes of Liraglutide. Since proteomics and metabolomics are ST:STUDY_SUMMARY complementary to each other in the context of the biological pathways, studying ST:STUDY_SUMMARY the metabolic impacts of Liraglutide on T2DM patients would add further ST:STUDY_SUMMARY information about the beneficial health outcomes of Liraglutide. Thus, herein, ST:STUDY_SUMMARY we performed an untargeted metabolomics approach for identifying metabolic ST:STUDY_SUMMARY pathways impacted by the treatment of Liraglutide in T2DM patients. Methods: ST:STUDY_SUMMARY Untargeted liquid chromatography coupled with mass spectrometry was used for ST:STUDY_SUMMARY metabolomics analysis of plasma samples collected from T2DM patients (n=20) ST:STUDY_SUMMARY before and after receiving Liraglutide treatment. Metabolic profiling and ST:STUDY_SUMMARY related pathway and network analyses were conducted. Results: The metabolic ST:STUDY_SUMMARY profiling analyses identified 93 endogenous metabolites were significantly ST:STUDY_SUMMARY affected by the Liraglutide treatments, which 49 metabolites up-regulated and 44 ST:STUDY_SUMMARY metabolites down-regulated. Moreover, the metabolic pathway analyses revealed ST:STUDY_SUMMARY that the most pronounced metabolite and metabolic pathways that were affected by ST:STUDY_SUMMARY the Liraglutide treatment was Pentose and glucuronate interconversion, ST:STUDY_SUMMARY suggesting the last may be a potential target of the Liraglutide treatment could ST:STUDY_SUMMARY be involved in part in the beneficial effects seen in T2DM patients, specially, ST:STUDY_SUMMARY we found that glucuronate interconversion pathway which is known by its role in ST:STUDY_SUMMARY eliminating toxic and undesirable substances from the human body, impacted in ST:STUDY_SUMMARY Liraglutide treated patients. The last findings ar consistence with our previous ST:STUDY_SUMMARY proteomics findings. Conclusion: These findings, taken together with our ST:STUDY_SUMMARY previous results, provide a deeper understanding of the underlying mechanisms ST:STUDY_SUMMARY involved in the beneficial effects of Liraglutide at the proteomic and metabolic ST:STUDY_SUMMARY levels in T2DM patients. ST:INSTITUTE King Faisal Specialist Hospital and Research Centre (KFSHRC) ST:LAST_NAME Al Mogren ST:FIRST_NAME Maha ST:ADDRESS Zahrawi Street, Al Maather, Riyadh 11211, Saudi Arabia ST:EMAIL malmogren@alfaisal.edu ST:PHONE 966541205332 ST:SUBMIT_DATE 2023-11-03 #SUBJECT SU:SUBJECT_TYPE Human SU:SUBJECT_SPECIES Homo sapiens SU:TAXONOMY_ID 9606 SU:GENDER Male #SUBJECT_SAMPLE_FACTORS: SUBJECT(optional)[tab]SAMPLE[tab]FACTORS(NAME:VALUE pairs separated by |)[tab]Additional sample data SUBJECT_SAMPLE_FACTORS - V1-1 Factor:Post-treatment RAW_FILE_NAME=V1-1 SUBJECT_SAMPLE_FACTORS - V1-10 Factor:Post-treatment RAW_FILE_NAME=V1-10 SUBJECT_SAMPLE_FACTORS - V1-11 Factor:Post-treatment RAW_FILE_NAME=V1-11 SUBJECT_SAMPLE_FACTORS - V1-12 Factor:Post-treatment RAW_FILE_NAME=V1-12 SUBJECT_SAMPLE_FACTORS - V1-13 Factor:Post-treatment RAW_FILE_NAME=V1-13 SUBJECT_SAMPLE_FACTORS - V1-14 Factor:Post-treatment RAW_FILE_NAME=V1-14 SUBJECT_SAMPLE_FACTORS - V1-15 Factor:Post-treatment RAW_FILE_NAME=V1-15 SUBJECT_SAMPLE_FACTORS - V1-16 Factor:Post-treatment RAW_FILE_NAME=V1-16 SUBJECT_SAMPLE_FACTORS - V1-17 Factor:Post-treatment RAW_FILE_NAME=V1-17 SUBJECT_SAMPLE_FACTORS - V1-18 Factor:Post-treatment RAW_FILE_NAME=V1-18 SUBJECT_SAMPLE_FACTORS - V1-19 Factor:Post-treatment RAW_FILE_NAME=V1-19 SUBJECT_SAMPLE_FACTORS - V1-2 Factor:Post-treatment RAW_FILE_NAME=V1-2 SUBJECT_SAMPLE_FACTORS - V1-20 Factor:Post-treatment RAW_FILE_NAME=V1-20 SUBJECT_SAMPLE_FACTORS - V1-21 Factor:Post-treatment RAW_FILE_NAME=V1-21 SUBJECT_SAMPLE_FACTORS - V1-22 Factor:Post-treatment RAW_FILE_NAME=V1-22 SUBJECT_SAMPLE_FACTORS - V1-25 Factor:Post-treatment RAW_FILE_NAME=V1-25 SUBJECT_SAMPLE_FACTORS - V1-28 Factor:Post-treatment RAW_FILE_NAME=V1-28 SUBJECT_SAMPLE_FACTORS - V1-3 Factor:Post-treatment RAW_FILE_NAME=V1-3 SUBJECT_SAMPLE_FACTORS - V1-4 Factor:Post-treatment RAW_FILE_NAME=V1-4 SUBJECT_SAMPLE_FACTORS - V1-6 Factor:Post-treatment RAW_FILE_NAME=V1-6 SUBJECT_SAMPLE_FACTORS - V1-7 Factor:Post-treatment RAW_FILE_NAME=V1-7 SUBJECT_SAMPLE_FACTORS - V1-8 Factor:Post-treatment RAW_FILE_NAME=V1-8 SUBJECT_SAMPLE_FACTORS - V1-9 Factor:Post-treatment RAW_FILE_NAME=V1-9 SUBJECT_SAMPLE_FACTORS - V0-1 Factor:Pre-treatment RAW_FILE_NAME=V0-1 SUBJECT_SAMPLE_FACTORS - V0-10 Factor:Pre-treatment RAW_FILE_NAME=V0-10 SUBJECT_SAMPLE_FACTORS - V0-11 Factor:Pre-treatment RAW_FILE_NAME=V0-11 SUBJECT_SAMPLE_FACTORS - V0-12 Factor:Pre-treatment RAW_FILE_NAME=V0-12 SUBJECT_SAMPLE_FACTORS - V0-13 Factor:Pre-treatment RAW_FILE_NAME=V0-13 SUBJECT_SAMPLE_FACTORS - V0-14 Factor:Pre-treatment RAW_FILE_NAME=V0-14 SUBJECT_SAMPLE_FACTORS - V0-15 Factor:Pre-treatment RAW_FILE_NAME=V0-15 SUBJECT_SAMPLE_FACTORS - V0-16 Factor:Pre-treatment RAW_FILE_NAME=V0-16 SUBJECT_SAMPLE_FACTORS - V0-17 Factor:Pre-treatment RAW_FILE_NAME=V0-17 SUBJECT_SAMPLE_FACTORS - V0-18 Factor:Pre-treatment RAW_FILE_NAME=V0-18 SUBJECT_SAMPLE_FACTORS - V0-19 Factor:Pre-treatment RAW_FILE_NAME=V0-19 SUBJECT_SAMPLE_FACTORS - V0-2 Factor:Pre-treatment RAW_FILE_NAME=V0-2 SUBJECT_SAMPLE_FACTORS - V0-20 Factor:Pre-treatment RAW_FILE_NAME=V0-20 SUBJECT_SAMPLE_FACTORS - V0-21 Factor:Pre-treatment RAW_FILE_NAME=V0-21 SUBJECT_SAMPLE_FACTORS - V0-22 Factor:Pre-treatment RAW_FILE_NAME=V0-22 SUBJECT_SAMPLE_FACTORS - V0-25 Factor:Pre-treatment RAW_FILE_NAME=V0-25 SUBJECT_SAMPLE_FACTORS - V0-28 Factor:Pre-treatment RAW_FILE_NAME=V0-28 SUBJECT_SAMPLE_FACTORS - V0-3 Factor:Pre-treatment RAW_FILE_NAME=V0-3 SUBJECT_SAMPLE_FACTORS - V0-4 Factor:Pre-treatment RAW_FILE_NAME=V0-4 SUBJECT_SAMPLE_FACTORS - V0-6 Factor:Pre-treatment RAW_FILE_NAME=V0-6 SUBJECT_SAMPLE_FACTORS - V0-7 Factor:Pre-treatment RAW_FILE_NAME=V0-7 SUBJECT_SAMPLE_FACTORS - V0-8 Factor:Pre-treatment RAW_FILE_NAME=V0-8 SUBJECT_SAMPLE_FACTORS - V0-9 Factor:Pre-treatment RAW_FILE_NAME=V0-9 #COLLECTION CO:COLLECTION_SUMMARY The study was approved by the Institutional Review Board of the College of CO:COLLECTION_SUMMARY Medicine, King Saud University, Riyadh, Saudi Arabia (registration no. CO:COLLECTION_SUMMARY E-18-3075). Recruited patients were asked to sign a written informed consent CO:COLLECTION_SUMMARY form before enrolling. Twenty patients who were diagnosed with T2DM were CO:COLLECTION_SUMMARY referred to the King Khaled University Hospital's (KKUH), Obesity Research CO:COLLECTION_SUMMARY Center, where this study took place. Patients were treated with an appropriate CO:COLLECTION_SUMMARY dose of Liraglutide for a three months as described previously (8). Samples were CO:COLLECTION_SUMMARY taken pre-treatment and post-treatment. Note: the T2DM participants were on CO:COLLECTION_SUMMARY other medications including insulin and metformin beside the Liraglutide CO:COLLECTION_SUMMARY treatment. CO:COLLECTION_PROTOCOL_ID Liraglutide_sample_collection.pdf CO:COLLECTION_PROTOCOL_FILENAME Liraglutide_sample_collection.pdf CO:SAMPLE_TYPE Blood (plasma) #TREATMENT TR:TREATMENT_SUMMARY Patients with indications of add-on liraglutide were started on treatment by TR:TREATMENT_SUMMARY their physician in a scaled-up dose from 0.6 mg to 1.8 mg of a once-daily TR:TREATMENT_SUMMARY subcutaneous injection over a period of three weeks. The follow-up visit was TR:TREATMENT_SUMMARY scheduled 3 months after receiving the full dose (1.8 mg) of liraglutide. Urine TR:TREATMENT_SUMMARY samples were collected at two time points: one sample before and another sample TR:TREATMENT_SUMMARY after treatment with liraglutide. Blood samples were collected by venipuncture TR:TREATMENT_SUMMARY into plain tubes (Vacutainer, BD Biosciences, San Jose, CA, USA) from each TR:TREATMENT_SUMMARY patient after a 10 h fast. The plasma was separated by centrifugation (15 min, TR:TREATMENT_SUMMARY 3000× g), divided into several aliquots, and stored at −80 °C for further TR:TREATMENT_SUMMARY analysis. TR:TREATMENT_COMPOUND Liraglutide #SAMPLEPREP SP:SAMPLEPREP_SUMMARY Metabolite extraction was performed as mentioned elsewhere [1]. Briefly,100 μL SP:SAMPLEPREP_SUMMARY aliquot of plasma was mixed with 900 μL of an extraction solvent 1:1 SP:SAMPLEPREP_SUMMARY acetonitrile (ACN): methanol (MeOH). Concurrently, quality control (QC) samples SP:SAMPLEPREP_SUMMARY were generated by taking aliquots from all samples to verify system stability. SP:SAMPLEPREP_SUMMARY The mixtures were agitated on a thermomixer (Eppendorf, CITY, Germany) at 600 SP:SAMPLEPREP_SUMMARY rpm and kept at room temperature (RT) for one hour. Subsequently, the samples SP:SAMPLEPREP_SUMMARY underwent centrifugation at 16000 rpm, at a temperature of 4ºC, for a duration SP:SAMPLEPREP_SUMMARY of 10 minutes. After centrifugation, 950 μL of the resultant supernatant was SP:SAMPLEPREP_SUMMARY transferred into a 1.5-ml Eppendorf tube and then subjected to complete SP:SAMPLEPREP_SUMMARY evaporation using a SpeedVac system (Christ, Germany). The dried samples were SP:SAMPLEPREP_SUMMARY reconstituted with 100 μL of a 50% mobile phase A and B (A: 0.1% Formic acid in SP:SAMPLEPREP_SUMMARY dH2O, B: 0.1% Formic acid in 50% ACN: MeOH). This reconstitution was followed by SP:SAMPLEPREP_SUMMARY brief vortexing and then introduced into the LC-MS system for analysis. SP:SAMPLEPREP_PROTOCOL_FILENAME Saxenda_Metabolite_Extraction.pdf #CHROMATOGRAPHY CH:CHROMATOGRAPHY_SUMMARY Waters Acquity UPLC system coupled with a Xevo G2-S QTOF mass spectrometer with CH:CHROMATOGRAPHY_SUMMARY an electrospray ionization source (ESI) was used to explore the metabolic CH:CHROMATOGRAPHY_SUMMARY profile. The extracted metabolites were separated using an ACQUITY UPLC using an CH:CHROMATOGRAPHY_SUMMARY XSelect column (100×2.1mm 2.5 μm) (Waters Ltd., Elstree, UK). Mobile phase CH:CHROMATOGRAPHY_SUMMARY solvent A was 0.1% formic acid in dH2O, while solvent B consisted of 0.1% formic CH:CHROMATOGRAPHY_SUMMARY acid in 50% ACN: MeOH. A gradient elution program was run: 0-16 min with 95-5% CH:CHROMATOGRAPHY_SUMMARY A, 16-19 min at 5% A, 19-20 min 5-95% A, and 20-22 min maintaining 5-95% A, all CH:CHROMATOGRAPHY_SUMMARY at a flow rate of 300 µL/min. MS spectra were obtained in both positive (ESI+) CH:CHROMATOGRAPHY_SUMMARY and negative (ESI-) electrospray ionization modes. The MS parameters were as CH:CHROMATOGRAPHY_SUMMARY follows: source temperature at 150°C, desolvation temperature at 500°C (ESI+) CH:CHROMATOGRAPHY_SUMMARY or 140°C (ESI-), capillary voltage at 3.20 kV (ESI+) or 3 kV (ESI-), cone CH:CHROMATOGRAPHY_SUMMARY voltage at 40 V, desolvation gas flow at 800.0 L/h, and cone gas flow at 50 L/h. CH:CHROMATOGRAPHY_SUMMARY Collision energies for low and high functions were set at off and 10 V to 50 V, CH:CHROMATOGRAPHY_SUMMARY respectively, in MSE mode. The mass spectrometer was calibrated using sodium CH:CHROMATOGRAPHY_SUMMARY formate in the 100–1200 Da range. Data were collected using Masslynx™ V4.1 CH:CHROMATOGRAPHY_SUMMARY workstation in continuum mode (Waters Inc., Milford, Massachusetts, USA). CH:METHODS_FILENAME Saxenda_LC_MS.pdf CH:INSTRUMENT_NAME Waters Acquity UPLC CH:COLUMN_NAME Waters XSelect HSS C18 (100 × 2.1mm,2.5um) CH:COLUMN_TEMPERATURE 55 CH:FLOW_GRADIENT 0-16 min 95- 5% A, 16-19 min 5% A, 19-20 min 5-95% A, 20-22 min 95- 95% A CH:FLOW_RATE 300 µL/min CH:SOLVENT_A 100% water; 0.1% formic acid CH:SOLVENT_B 50% methanol/50% acetonitrile; 0.1% formic acid CH:CHROMATOGRAPHY_TYPE Reversed phase #ANALYSIS AN:ANALYSIS_TYPE MS AN:ANALYSIS_PROTOCOL_FILE Saxenda_LC_MS.pdf #MS MS:INSTRUMENT_NAME Waters Xevo-G2-S MS:INSTRUMENT_TYPE QTOF MS:MS_TYPE ESI MS:MS_COMMENTS The DIA data were collected with a Masslynx™ V4.1 workstation in continuum MS:MS_COMMENTS mode (Waters Inc., Milford, MA, USA). The raw MS data were processed following a MS:MS_COMMENTS standard pipeline using the Progenesis QI v.3.0 software. MS:ION_MODE POSITIVE MS:MS_RESULTS_FILE ST003056_AN005010_Results.txt UNITS:Area Has m/z:Yes Has RT:Yes RT units:Minutes #END