#METABOLOMICS WORKBENCH abeerotb12_20231209_060007 DATATRACK_ID:4494 STUDY_ID:ST003171 ANALYSIS_ID:AN005205 PROJECT_ID:PR001971
VERSION             	1
CREATED_ON             	April 15, 2024, 6:12 pm
#PROJECT
PR:PROJECT_TITLE                 	Comberhincive Chemometric Metabolomic Profile for Maple Syrup Urine Disease Sick
PR:PROJECT_TITLE                 	Patients
PR:PROJECT_TYPE                  	Untargeted LCMS
PR:PROJECT_SUMMARY               	Abstract: Background: A malfunction in the activity of the branched-chain
PR:PROJECT_SUMMARY               	alpha-ketoacid dehydrogenase (BCKAD) complex results in maple syrup urine
PR:PROJECT_SUMMARY               	disease (MSUD), a genetically inherited illness. Three amino acids—leucine,
PR:PROJECT_SUMMARY               	isoleucine, and valine—are typically broken down by branched-chain alpha-keto
PR:PROJECT_SUMMARY               	acid dehydrogenase complex. Abnormal activity in this process, therefore, can
PR:PROJECT_SUMMARY               	affect vital body systems and result in metabolic dysregulation associated with
PR:PROJECT_SUMMARY               	the consequences of this disease. The therapy and follow-up of ill MSUD patients
PR:PROJECT_SUMMARY               	are greatly aided by many researched endogenous metabolites as well as
PR:PROJECT_SUMMARY               	dysregulated biomarkers and pathways. Objectives: Our goal is to add to the
PR:PROJECT_SUMMARY               	increasing knowledge of information about sick MSUD and the pathways that are
PR:PROJECT_SUMMARY               	involved in improving patient outcomes by utilizing untargeted metabolomics to
PR:PROJECT_SUMMARY               	examine the unique profile of MSUD in sick MSUD patients. Methods: This study
PR:PROJECT_SUMMARY               	evaluated the metabolic changes in the dry blood spot (DBS) of 14 sick MSUD
PR:PROJECT_SUMMARY               	patients and 14 healthy controls utilizing untargeted metabolomics studies
PR:PROJECT_SUMMARY               	performed with liquid chromatography–mass spectrometry. Findings: Based on
PR:PROJECT_SUMMARY               	metabolomics analysis,7754 metabolites were found to be highly dysregulated.Out
PR:PROJECT_SUMMARY               	of them,3716 were up-regulated and 4038 were down-regulated.1557 of the
PR:PROJECT_SUMMARY               	annotated metabolites were found to be endogenous metabolites. The research
PR:PROJECT_SUMMARY               	found possible biomarkers for MSUD, including Glutathioselenol and dUDP, which
PR:PROJECT_SUMMARY               	were elevated in sick MSUD relative to healthy controls and LysoPI downregulated
PR:PROJECT_SUMMARY               	in sick MSUD. Moreover, the Sphingolipid metabolism, selenocompound metabolism
PR:PROJECT_SUMMARY               	and porphyrin metabolism pathways were the most impacted in sick MSUD. In
PR:PROJECT_SUMMARY               	summary, our findings shows that metabolomics is a noninvasive approach to
PR:PROJECT_SUMMARY               	understanding the pathophysiology of the medical condition and a potentially
PR:PROJECT_SUMMARY               	useful technique for assessing novel biomarkers in the early detection of sick
PR:PROJECT_SUMMARY               	MSUD.Further research is required regarding the relationship of these
PR:PROJECT_SUMMARY               	dysregulated metabolites to compromised pathways.
PR:INSTITUTE                     	King Saud University
PR:DEPARTMENT                    	Biochemistry
PR:LABORATORY                    	Clinical Biochemistry
PR:LAST_NAME                     	AlOtaibi
PR:FIRST_NAME                    	Abeer
PR:ADDRESS                       	King Fahad road,Riyadh 11211, Saudi Arabia
PR:EMAIL                         	441203289@student.ksu.edu.sa
PR:PHONE                         	+966551933703
#STUDY
ST:STUDY_TITLE                   	Untargeted Metabolomics for Exploring Metabolomic Profile of Maple Syrup Urine
ST:STUDY_TITLE                   	Disease Sick Patients
ST:STUDY_TYPE                    	Untargeted LCMS
ST:STUDY_SUMMARY                 	Abstract non-newborn: Background: A malfunction in the activity of the
ST:STUDY_SUMMARY                 	branched-chain alpha-ketoacid dehydrogenase (BCKAD) complex results in maple
ST:STUDY_SUMMARY                 	syrup urine disease (MSUD), a genetically inherited illness. Three amino
ST:STUDY_SUMMARY                 	acids—leucine, isoleucine, and valine—are typically broken down by this
ST:STUDY_SUMMARY                 	complex. Abnormal activity in this process, therefore, can affect vital body
ST:STUDY_SUMMARY                 	systems and result in metabolic dysregulation associated with the consequences
ST:STUDY_SUMMARY                 	of the disease. The therapy and follow-up of ill MSUD patients are greatly aided
ST:STUDY_SUMMARY                 	by many researched endogenous metabolites as well as dysregulated biomarkers and
ST:STUDY_SUMMARY                 	pathways. Objectives: Our goal is to add to the increasing knowledge of
ST:STUDY_SUMMARY                 	information about sick MSUD with relation to MSUD newborns and the pathways that
ST:STUDY_SUMMARY                 	are involved in improving patient outcomes by utilizing untargeted metabolomics
ST:STUDY_SUMMARY                 	to examine the unique profile of MSUD in sick MSUD patients. Methods: This study
ST:STUDY_SUMMARY                 	evaluated the metabolic changes in the dry blood spot (DBS) of 14 sick MSUD
ST:STUDY_SUMMARY                 	patients and 14 healthy controls utilizing untargeted metabolomics studies
ST:STUDY_SUMMARY                 	performed with liquid chromatography–mass spectrometry. Findings: Based on
ST:STUDY_SUMMARY                 	metabolomics analysis,7754 metabolites were found to be highly dysregulated.Out
ST:STUDY_SUMMARY                 	of them,3716 were up-regulated and 4038 were down-regulated.1557 of the
ST:STUDY_SUMMARY                 	annotated metabolites were found to be endogenous metabolites. The research
ST:STUDY_SUMMARY                 	found possible biomarkers for MSUD, including Glutathioselenol and dUDP, which
ST:STUDY_SUMMARY                 	were elevated in sick MSUD relative to healthy controls and LysoPI downregulated
ST:STUDY_SUMMARY                 	in sick MSUD. Moreover, the Sphingolipid metabolism, selenocompound metabolism
ST:STUDY_SUMMARY                 	and porphyrin metabolism pathways were the most impacted in MSUD newborns.This
ST:STUDY_SUMMARY                 	study shows 92 endogenous metabolites between newborn MSUD and sick MSUD. In
ST:STUDY_SUMMARY                 	summary, our findings shows that metabolomics is a noninvasive approach to
ST:STUDY_SUMMARY                 	understanding the pathophysiology of the medical condition and a potentially
ST:STUDY_SUMMARY                 	useful technique for assessing novel biomarkers in the early detection of sick
ST:STUDY_SUMMARY                 	MSUD.Further research is required regarding the relationship of these
ST:STUDY_SUMMARY                 	dysregulated metabolites to compromised pathways.
ST:INSTITUTE                     	King Saud University
ST:DEPARTMENT                    	Biochemistry
ST:LABORATORY                    	Clinical Biochemistry
ST:LAST_NAME                     	AlOtaibi
ST:FIRST_NAME                    	Abeer
ST:ADDRESS                       	2808
ST:EMAIL                         	441203289@student.ksu.edu.sa
ST:PHONE                         	+966551933703
ST:NUM_GROUPS                    	2
ST:TOTAL_SUBJECTS                	28
ST:NUM_MALES                     	7
ST:NUM_FEMALES                   	7
#SUBJECT
SU:SUBJECT_TYPE                  	Human
SU:SUBJECT_SPECIES               	Homo sapiens
SU:TAXONOMY_ID                   	9606
SU:AGE_OR_AGE_RANGE              	>14 days,
SU:GENDER                        	Male and female
SU:HUMAN_INCLUSION_CRITERIA      	>14 days, MSUD sick patients DBS
SU:HUMAN_EXCLUSION_CRITERIA      	</=14 days, any IEM's sick other than MSUD, unknown gender
#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           	-	20820068	Sample source:Whole blood | Sex:M | sample_type:Control	age_years=18; RAW_FILE_NAME(Raw file name)=20820068_nNC_p; RAW_FILE_NAME(Raw file name)=20820068_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	20830764	Sample source:Whole blood | Sex:M | sample_type:Control	age_years=14; RAW_FILE_NAME(Raw file name)=20830764_nNC_p; RAW_FILE_NAME(Raw file name)=20830764_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	20830816	Sample source:Whole blood | Sex:M | sample_type:Control	age_years=10; RAW_FILE_NAME(Raw file name)=20830816_nNC_p; RAW_FILE_NAME(Raw file name)=20830816_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	20839516	Sample source:Whole blood | Sex:F | sample_type:Control	age_years=11; RAW_FILE_NAME(Raw file name)=20839516_nNC_p; RAW_FILE_NAME(Raw file name)=20839516_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21273683	Sample source:Whole blood | Sex:F | sample_type:Control	age_years=11; RAW_FILE_NAME(Raw file name)=21273683_nNC_p; RAW_FILE_NAME(Raw file name)=21273683_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21489196	Sample source:Whole blood | Sex:F | sample_type:Control	age_years=11; RAW_FILE_NAME(Raw file name)=21489196_nNC_p; RAW_FILE_NAME(Raw file name)=21489196_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21489309	Sample source:Whole blood | Sex:F | sample_type:Control	age_years=13; RAW_FILE_NAME(Raw file name)=21489309_nNC_p; RAW_FILE_NAME(Raw file name)=21489309_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21489947	Sample source:Whole blood | Sex:M | sample_type:Control	age_years=10; RAW_FILE_NAME(Raw file name)=21489947_nNC_p; RAW_FILE_NAME(Raw file name)=21489947_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21532106	Sample source:Whole blood | Sex:M | sample_type:Control	age_years=11; RAW_FILE_NAME(Raw file name)=21532106_nNC_p; RAW_FILE_NAME(Raw file name)=21532106_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21581573	Sample source:Whole blood | Sex:M | sample_type:Control	age_years=8; RAW_FILE_NAME(Raw file name)=21581573_nNC_p; RAW_FILE_NAME(Raw file name)=21581573_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21695964	Sample source:Whole blood | Sex:F | sample_type:Control	age_years=10; RAW_FILE_NAME(Raw file name)=21695964_nNC_p; RAW_FILE_NAME(Raw file name)=21695964_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21796397	Sample source:Whole blood | Sex:F | sample_type:Control	age_years=12; RAW_FILE_NAME(Raw file name)=21796397_nNC_p; RAW_FILE_NAME(Raw file name)=21796397_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21799570	Sample source:Whole blood | Sex:F | sample_type:Control	age_years=17; RAW_FILE_NAME(Raw file name)=21799570_nNC_p; RAW_FILE_NAME(Raw file name)=21799570_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	21800326	Sample source:Whole blood | Sex:F | sample_type:Control	age_years=4; RAW_FILE_NAME(Raw file name)=21800326_nNC_p; RAW_FILE_NAME(Raw file name)=21800326_nNC_N
SUBJECT_SAMPLE_FACTORS           	-	148705	Sample source:Whole blood | Sex:M | sample_type:MSUD	age_years=10; RAW_FILE_NAME(Raw file name)=148705_nNM_P; RAW_FILE_NAME(Raw file name)=148705_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	15383554	Sample source:Whole blood | Sex:M | sample_type:MSUD	age_years=15; RAW_FILE_NAME(Raw file name)=15383554_nNM_P; RAW_FILE_NAME(Raw file name)=15383554_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	20613149	Sample source:Whole blood | Sex:F | sample_type:MSUD	age_years=1; RAW_FILE_NAME(Raw file name)=20613149_nNM_P; RAW_FILE_NAME(Raw file name)=20613149_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21100943	Sample source:Whole blood | Sex:F | sample_type:MSUD	age_years=6; RAW_FILE_NAME(Raw file name)=21100943_nNM_P; RAW_FILE_NAME(Raw file name)=21100943_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21219108	Sample source:Whole blood | Sex:M | sample_type:MSUD	age_years=0.27; RAW_FILE_NAME(Raw file name)=21219108_nNM_P; RAW_FILE_NAME(Raw file name)=21219108_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21770104	Sample source:Whole blood | Sex:F | sample_type:MSUD	age_years=16; RAW_FILE_NAME(Raw file name)=21770104_nNM_P; RAW_FILE_NAME(Raw file name)=21770104_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21776205	Sample source:Whole blood | Sex:M | sample_type:MSUD	age_years=18; RAW_FILE_NAME(Raw file name)=21776205_nNM_P; RAW_FILE_NAME(Raw file name)=21776205_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21796944	Sample source:Whole blood | Sex:M | sample_type:MSUD	age_years=14; RAW_FILE_NAME(Raw file name)=21796944_nNM_P; RAW_FILE_NAME(Raw file name)=21796944_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21799172	Sample source:Whole blood | Sex:F | sample_type:MSUD	age_years=14; RAW_FILE_NAME(Raw file name)=21799172_nNM_P; RAW_FILE_NAME(Raw file name)=21799172_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21805181	Sample source:Whole blood | Sex:F | sample_type:MSUD	age_years=16; RAW_FILE_NAME(Raw file name)=21805181_nNM_P; RAW_FILE_NAME(Raw file name)=21805181_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21833519	Sample source:Whole blood | Sex:M | sample_type:MSUD	age_years=18; RAW_FILE_NAME(Raw file name)=21833519_nNM_P; RAW_FILE_NAME(Raw file name)=21833519_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21914504	Sample source:Whole blood | Sex:M | sample_type:MSUD	age_years=17; RAW_FILE_NAME(Raw file name)=21914504_nNM_P; RAW_FILE_NAME(Raw file name)=21914504_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	27339556	Sample source:Whole blood | Sex:F | sample_type:MSUD	age_years=9; RAW_FILE_NAME(Raw file name)=27339556_nNM_P; RAW_FILE_NAME(Raw file name)=27339556_nNM_N
SUBJECT_SAMPLE_FACTORS           	-	21460012	Sample source:Whole blood | Sex:F | sample_type:MSUD	age_years=8; RAW_FILE_NAME(Raw file name)=21460012_nNM_P; RAW_FILE_NAME(Raw file name)=21460012_nNM_N
#COLLECTION
CO:COLLECTION_SUMMARY            	Twenty-eight DBS samples were collected from biochemically and genetically
CO:COLLECTION_SUMMARY            	confirmed MSUD sick patients (n=14) at King Faisal Specialist Hospital and
CO:COLLECTION_SUMMARY            	Research Center (KFSHRC) and healthy controls (n=14). These healthy individuals
CO:COLLECTION_SUMMARY            	were almost age-sex matched with MSUD's group (Female 50%). Samples from newborn
CO:COLLECTION_SUMMARY            	patients and controls less than 14 days were excluded from this study, as well
CO:COLLECTION_SUMMARY            	as any IEM other than MSUD excluded.
CO:SAMPLE_TYPE                   	Blood (whole)
CO:STORAGE_CONDITIONS            	-80℃
#TREATMENT
TR:TREATMENT_SUMMARY             	No treatment used.
#SAMPLEPREP
SP:SAMPLEPREP_SUMMARY            	One punch, of size 3.3mm, DBS from MSUD newborn and healthy controls were
SP:SAMPLEPREP_SUMMARY            	distributed in 96 V-shaped plate wells, then immersed with 250 μL of extraction
SP:SAMPLEPREP_SUMMARY            	solvent composed of 20% Water: 20% MeOH:40% ACN. The samples were vortexed in
SP:SAMPLEPREP_SUMMARY            	thermomixer (Eppendrof, Germany) at 600 rpm, 25˚C, for 2hrs. The samples were
SP:SAMPLEPREP_SUMMARY            	spun down at 16.000 rpm, 4˚C, for 10 min. The supernatants were transferred
SP:SAMPLEPREP_SUMMARY            	into new 96 V-shaped plate and the punches discarded, and then the samples were
SP:SAMPLEPREP_SUMMARY            	dried in a vacuum concentrator SpeedVac (Christ, City, Germany). Dry residue was
SP:SAMPLEPREP_SUMMARY            	re-dissolved in 100 μL of methanol/water with a ratio (1:1) prior to LC-MS
SP:SAMPLEPREP_SUMMARY            	analysis.
SP:SAMPLEPREP_PROTOCOL_FILENAME  	MSUD_Metabolites_Extraction.pdf
SP:PROCESSING_STORAGE_CONDITIONS 	Room temperature
SP:EXTRACT_STORAGE               	Room temperature
#CHROMATOGRAPHY
CH:CHROMATOGRAPHY_TYPE           	Reversed phase
CH:INSTRUMENT_NAME               	Waters Acquity UPLC
CH:COLUMN_NAME                   	Waters XSelect CSH C18 (100 x 2.1mm 2.5um)
CH:SOLVENT_A                     	100% water; 0.1% formic acid
CH:SOLVENT_B                     	50% MeOH/50% ACN; 0.1% formic acid
CH:FLOW_GRADIENT                 	95–5% A [0–16 min], 5% A [16–19 min], 5–95% A [19–20 min], and
CH:FLOW_GRADIENT                 	95–95% A [20–22 min].
CH:FLOW_RATE                     	300 μL/min
CH:COLUMN_TEMPERATURE            	55
CH:METHODS_FILENAME              	MSUD_LC_MS_Metabolomics.pdf
#ANALYSIS
AN:ANALYSIS_TYPE                 	MS
AN:ANALYSIS_PROTOCOL_FILE        	Metabolomics_Pos_and_Neg.pdf
#MS
MS:INSTRUMENT_NAME               	Waters Xevo-G2-S
MS:INSTRUMENT_TYPE               	QTOF
MS:MS_TYPE                       	ESI
MS:ION_MODE                      	NEGATIVE
MS:MS_COMMENTS                   	The DIA data were gathered with a Masslynx™ V4.1 Software (Waters Inc.,
MS:MS_COMMENTS                   	Milford, MA, USA) in continuum mode. Quality control samples (QCs) were made
MS:MS_COMMENTS                   	with aliquots from all samples and introduced to the instrument after the
MS:MS_COMMENTS                   	randomization of each group, after 10 samples to validate the stability of the
MS:MS_COMMENTS                   	system (Aldubayan, Rodan, Berry, & Levy, 2017). Data and Statistical Analyses:
MS:MS_COMMENTS                   	The raw MS data were processed using a standard pipeline, beginning from an
MS:MS_COMMENTS                   	alignment depending on the mass to charge ratio (m/s) and the retention time
MS:MS_COMMENTS                   	(RT) of ion signals’, picking the best peak, followed by the filtering of
MS:MS_COMMENTS                   	signal depending on the quality of peak by utilizing the Progenesis QI (v.3.0)
MS:MS_COMMENTS                   	software (Waters Technologies, Milford, MA, USA). A multivariate statistics was
MS:MS_COMMENTS                   	applied by using MetaboAnalyst (v.5.0) (McGill University, Montreal, QB, Canada)
MS:MS_COMMENTS                   	(http://www.metaboanalyst.ca) (Pang et al., 2021). All the imported data-groups
MS:MS_COMMENTS                   	(compounds’ names also their raw abundances information) were Pareto scaled,
MS:MS_COMMENTS                   	log transformed and applied for creating partial least squares discriminant
MS:MS_COMMENTS                   	analysis (PLS-DA) and orthogonal partial least squares discriminant analysis
MS:MS_COMMENTS                   	(OPLS-DA) models. The generated OPLS-DA model was measured through R2Y and Q2
MS:MS_COMMENTS                   	values, that represents the fitness of the model and predictive ability,
MS:MS_COMMENTS                   	respectively (Worley & Powers, 2013). A univariate analysis was applied through
MS:MS_COMMENTS                   	Mass Profiler Professional (MPP) (v. 15.0) software (Agilent, Santa Clara, CA,
MS:MS_COMMENTS                   	USA). A volcano plot was applied to uncover significantly changed mass features
MS:MS_COMMENTS                   	based on a Moderated T-test, cut-off: no correction, p <0.05, FC 1.5. Heatmap
MS:MS_COMMENTS                   	analysis for altered features was performed using the Pearson distance measure
MS:MS_COMMENTS                   	according to the Pearson similarity test (Gu et al., 2020).
MS:MS_RESULTS_FILE               	ST003171_AN005205_Results.txt	UNITS:Peak area	Has m/z:Yes	Has RT:Yes	RT units:Seconds
#END