#METABOLOMICS WORKBENCH Mahamogren_20230529_060250 DATATRACK_ID:4052 STUDY_ID:ST002735 ANALYSIS_ID:AN004434 PROJECT_ID:PR001699
VERSION             	1
CREATED_ON             	June 12, 2023, 10:41 am
#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
#STUDY
ST:STUDY_TITLE                   	Untargeted metabolomics revealed multiple metabolic perturbations in plasma of
ST:STUDY_TITLE                   	T2D patients in response to Liraglutide
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
#SUBJECT
SU:SUBJECT_TYPE                  	Human
SU:SUBJECT_SPECIES               	Homo sapiens
SU:TAXONOMY_ID                   	9606
SU:GENDER                        	Male
#FACTORS
#SUBJECT_SAMPLE_FACTORS:         	SUBJECT(optional)[tab]SAMPLE[tab]FACTORS(NAME:VALUE pairs separated by |)[tab]Raw file names and additional sample data
SUBJECT_SAMPLE_FACTORS           	-	RS_1	Factor:Pre-treatment	RAW_FILE_NAME=RS_1
SUBJECT_SAMPLE_FACTORS           	-	RS_2	Factor:Pre-treatment	RAW_FILE_NAME=RS_2
SUBJECT_SAMPLE_FACTORS           	-	RS_3	Factor:Pre-treatment	RAW_FILE_NAME=RS_3
SUBJECT_SAMPLE_FACTORS           	-	RS_4	Factor:Pre-treatment	RAW_FILE_NAME=RS_4
SUBJECT_SAMPLE_FACTORS           	-	RS_5	Factor:Pre-treatment	RAW_FILE_NAME=RS_5
SUBJECT_SAMPLE_FACTORS           	-	RS_6	Factor:Pre-treatment	RAW_FILE_NAME=RS_6
SUBJECT_SAMPLE_FACTORS           	-	RS_7	Factor:Pre-treatment	RAW_FILE_NAME=RS_7
SUBJECT_SAMPLE_FACTORS           	-	RS_8	Factor:Pre-treatment	RAW_FILE_NAME=RS_8
SUBJECT_SAMPLE_FACTORS           	-	RS_9	Factor:Pre-treatment	RAW_FILE_NAME=RS_9
SUBJECT_SAMPLE_FACTORS           	-	RS_10	Factor:Pre-treatment	RAW_FILE_NAME=RS_10
SUBJECT_SAMPLE_FACTORS           	-	RS_11	Factor:Pre-treatment	RAW_FILE_NAME=RS_11
SUBJECT_SAMPLE_FACTORS           	-	RS_12	Factor:Pre-treatment	RAW_FILE_NAME=RS_12
SUBJECT_SAMPLE_FACTORS           	-	RS_13	Factor:Pre-treatment	RAW_FILE_NAME=RS_13
SUBJECT_SAMPLE_FACTORS           	-	RS_14	Factor:Pre-treatment	RAW_FILE_NAME=RS_14
SUBJECT_SAMPLE_FACTORS           	-	RS_15	Factor:Pre-treatment	RAW_FILE_NAME=RS_15
SUBJECT_SAMPLE_FACTORS           	-	RS_16	Factor:Pre-treatment	RAW_FILE_NAME=RS_16
SUBJECT_SAMPLE_FACTORS           	-	RS_17	Factor:Pre-treatment	RAW_FILE_NAME=RS_17
SUBJECT_SAMPLE_FACTORS           	-	RS_18	Factor:Pre-treatment	RAW_FILE_NAME=RS_18
SUBJECT_SAMPLE_FACTORS           	-	RS_19	Factor:Pre-treatment	RAW_FILE_NAME=RS_19
SUBJECT_SAMPLE_FACTORS           	-	RS_20	Factor:Pre-treatment	RAW_FILE_NAME=RS_20
SUBJECT_SAMPLE_FACTORS           	-	RS_P1	Factor:Post-treatment	RAW_FILE_NAME=RS_P1
SUBJECT_SAMPLE_FACTORS           	-	RS_P2	Factor:Post-treatment	RAW_FILE_NAME=RS_P2
SUBJECT_SAMPLE_FACTORS           	-	RS_P3	Factor:Post-treatment	RAW_FILE_NAME=RS_P3
SUBJECT_SAMPLE_FACTORS           	-	RS_P4	Factor:Post-treatment	RAW_FILE_NAME=RS_P4
SUBJECT_SAMPLE_FACTORS           	-	RS_P5	Factor:Post-treatment	RAW_FILE_NAME=RS_P5
SUBJECT_SAMPLE_FACTORS           	-	RS_P6	Factor:Post-treatment	RAW_FILE_NAME=RS_P6
SUBJECT_SAMPLE_FACTORS           	-	RS_P7	Factor:Post-treatment	RAW_FILE_NAME=RS_P7
SUBJECT_SAMPLE_FACTORS           	-	RS_P8	Factor:Post-treatment	RAW_FILE_NAME=RS_P8
SUBJECT_SAMPLE_FACTORS           	-	RS_P9	Factor:Post-treatment	RAW_FILE_NAME=RS_P9
SUBJECT_SAMPLE_FACTORS           	-	RS_P10	Factor:Post-treatment	RAW_FILE_NAME=RS_P10
SUBJECT_SAMPLE_FACTORS           	-	RS_P11	Factor:Post-treatment	RAW_FILE_NAME=RS_P11
SUBJECT_SAMPLE_FACTORS           	-	RS_P12	Factor:Post-treatment	RAW_FILE_NAME=RS_P12
SUBJECT_SAMPLE_FACTORS           	-	RS_P13	Factor:Post-treatment	RAW_FILE_NAME=RS_P13
SUBJECT_SAMPLE_FACTORS           	-	RS_P14	Factor:Post-treatment	RAW_FILE_NAME=RS_P14
SUBJECT_SAMPLE_FACTORS           	-	RS_P15	Factor:Post-treatment	RAW_FILE_NAME=RS_P15
SUBJECT_SAMPLE_FACTORS           	-	RS_P16	Factor:Post-treatment	RAW_FILE_NAME=RS_P16
SUBJECT_SAMPLE_FACTORS           	-	RS_P17	Factor:Post-treatment	RAW_FILE_NAME=RS_P17
SUBJECT_SAMPLE_FACTORS           	-	RS_P18	Factor:Post-treatment	RAW_FILE_NAME=RS_P18
SUBJECT_SAMPLE_FACTORS           	-	RS_P19	Factor:Post-treatment	RAW_FILE_NAME=RS_P19
SUBJECT_SAMPLE_FACTORS           	-	RS_P20	Factor:Post-treatment	RAW_FILE_NAME=RS_P20
#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: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            	Metabolites were extracted from plasma were collected from 20 type2 diabetic
SP:SAMPLEPREP_SUMMARY            	patients, pre-and post-treatment with liraglutide (n=40 samples) (10). Briefly,
SP:SAMPLEPREP_SUMMARY            	100 μL plasma sample were mixed with 900 μL of extraction solvent 50%
SP:SAMPLEPREP_SUMMARY            	acetonitrile (ACN) in methanol (MeOH). Meanwhile, QC samples were prepared with
SP:SAMPLEPREP_SUMMARY            	aliquots from all samples to check for system stability. The mixtures were mixed
SP:SAMPLEPREP_SUMMARY            	on thermomixer at 600 rpm at room temperature for one hour (Eppendorf, CITY,
SP:SAMPLEPREP_SUMMARY            	Germany). Afterward, the samples were centrifuged at 16000 rpm at 4ºC for 10
SP:SAMPLEPREP_SUMMARY            	min. The supernatant was transferred into new Eppendrof tube, and then
SP:SAMPLEPREP_SUMMARY            	evaporated completely in a SpeedVac (Christ, Germany). The dried samples were
SP:SAMPLEPREP_SUMMARY            	reconstituted with100 μl of 50% mobile phase A: B (A: 0.1% Formic acid in dH2O,
SP:SAMPLEPREP_SUMMARY            	B: 0.1% Formic acid in 50% ACN: MeOH).
#CHROMATOGRAPHY
CH:CHROMATOGRAPHY_TYPE           	Reversed phase
CH:INSTRUMENT_NAME               	Waters Acquity UPLC
CH:COLUMN_NAME                   	Waters XSelect HSS C18 (100 × 2.1mm,2.5um)
CH:SOLVENT_A                     	0.1% formic acid in dH2O
CH:SOLVENT_B                     	0.1% formic acid in 50% MeOH and ACN
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:COLUMN_TEMPERATURE            	55
#ANALYSIS
AN:ANALYSIS_TYPE                 	MS
#MS
MS:INSTRUMENT_NAME               	Waters Xevo-G2-S
MS:INSTRUMENT_TYPE               	QTOF
MS:MS_TYPE                       	ESI
MS:ION_MODE                      	POSITIVE
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:MS_RESULTS_FILE               	ST002735_AN004434_Results.txt	UNITS:Peak area	Has m/z:Yes	Has RT:Yes	RT units:Minutes
#END