Metabolomics Workbench : NIH Data Repository

MB Sample ID: SA220393

Local Sample ID:	P46_V1
Subject ID:	SU002382
Subject Type:	Human
Subject Species:	Homo sapiens
Taxonomy ID:	9606

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Subject:

Subject ID:	SU002382
Subject Type:	Human
Subject Species:	Homo sapiens
Taxonomy ID:	9606

Factors:

Local Sample ID	MB Sample ID	Factor Level ID	Level Value	Factor Name
P46_V1	SA220393	FL027474	Treated	Trial arm

Collection:

Collection ID:	CO002375
Collection Summary:	Serum and urine samples were collected at the three study sites; Liverpool, Paris and Piešťany. Samples collected at Paris and Piešťany were transported frozen to the Royal Liverpool University Hospital for metabolite analysis and storage at -80 °C. Serum samples (S-monovette, Sarstedt, Germany) were collected from patients after an overnight fast (≥8 h). Samples were centrifuged at 1500 ×g for 10 min at 4 °C; and the supernatant was stored at -20 °C until analysis.
Sample Type:	Blood (serum)
Storage Conditions:	-20℃

Treatment:

Treatment ID:	TR002394
Treatment Summary:	Samples studied were from patients partaking in the SONIA 2 clinical trial of nitisinone in AKU. SONIA 2 was a 4-year, open-label, evaluator-blind, randomised, no treatment controlled, parallel-group study undertaken at three study sites; Liverpool (UK), Paris (France) and Piešťany (Slovakia). The details and outcomes of the trial are published (1). Serum and urine samples were collected from participants at baseline (pre-treatment) then at 3 months and 1, 2, 3 and 4 years on 10 mg oral daily nitisinone (Orfadin®) treatment or no treatment. The serum and urine samples from visit 1 (baseline; pre-treatment), visit 4 (2 years), visit 6 (4 years) underwent metabolomic analysis. In this study, only the data from patients with samples available for these three time points were included; 53 and 50 patients in treated and untreated groups respectively for urine, and 47 and 45 patients in treated and untreated groups respectively for serum. Reference: (1) Ranganath, L.R.; Psarelli, E.E.; Arnoux, J.B.; Braconi, D.; Briggs, M.; Bröijersén, A.; Loftus, N.; Bygott, H.; Cox, T.F.; Davison, A.S.; et al. Efficacy and Safety of Once-Daily Nitisinone for Patients with Alkaptonuria (SONIA 2): An International, Multicentre, Open-Label, Randomised Controlled Trial. Lancet Diabetes Endocrinol. 2020, 8, 762–772, doi:10.1016/S2213-8587(20)30228-X.
Treatment Protocol ID:	Clinical trial ID: EudraCT no. 2013-001633-41
Treatment Compound:	Nitisinone (NTBC)
Treatment Dose:	10 mg daily
Treatment Doseduration:	48 months total

Sample Preparation:

Sampleprep ID:	SP002388
Sampleprep Summary:	Serum samples were prepared using the Agilent Bravo metabolomics platform. This automated platform was programmed to pipette 100 µL of serum into a 96-well plate from a 96-well plate that contained 200 µL of serum. Following this, 450 μL of a 1:1 mixture of methanol:ethanol was added to the plate to precipitate proteins. The supernatant was then applied to a Captiva EMR-lipid 96-well plate and left to stand for 5 min and a vacuum was applied to the plate (2-5 Hg) to initiate flow. Eluents were collected into 1 mL 96-well plates and subsequently dried under a stream of nitrogen. Prior to analysis, samples were reconstituted with 100 µL of 10 % methanol and were agitated on a plate shaker (MTS 2/4m IKA) at 600 rpm for 10 min.

Sampleprep ID:

SP002388

Sampleprep Summary:

Serum samples were prepared using the Agilent Bravo metabolomics platform. This automated platform was programmed to pipette 100 µL of serum into a 96-well plate from a 96-well plate that contained 200 µL of serum. Following this, 450 μL of a 1:1 mixture of methanol:ethanol was added to the plate to precipitate proteins. The supernatant was then applied to a Captiva EMR-lipid 96-well plate and left to stand for 5 min and a vacuum was applied to the plate (2-5 Hg) to initiate flow. Eluents were collected into 1 mL 96-well plates and subsequently dried under a stream of nitrogen. Prior to analysis, samples were reconstituted with 100 µL of 10 % methanol and were agitated on a plate shaker (MTS 2/4m IKA) at 600 rpm for 10 min.

Combined analysis:

Analysis ID	AN003750	AN003751
Analysis type	MS	MS
Chromatography type	Reversed phase	Reversed phase
Chromatography system	Agilent 1290 Infinity II	Agilent 1290 Infinity II
Column	Waters Atlantis dC18 (100 x 3mm,3um)	Waters Atlantis dC18 (100 x 3mm,3um)
MS Type	ESI	ESI
MS instrument type	QTOF	QTOF
MS instrument name	Agilent 6550 QTOF	Agilent 6550 QTOF
Ion Mode	NEGATIVE	POSITIVE
Units	peak area (pareto-scaled, log2-transformed)	peak area (pareto-scaled, log2-transformed)

Chromatography:

Chromatography ID:	CH002776
Chromatography Summary:	Analysis of serum and urine samples was performed using a published LC-QTOF-MS acquisition method, which employed a 1290 Infinity II HPLC coupled to a 6550 QTOF-MS equipped with dual AJS electrospray ionisation source (Agilent, Cheadle, UK). Data acquisition parameters are detailed in brief below and in full in Supplementary Materials. Reversed-phase LC was performed on an Atlantis dC18 column (3×100 mm, 3 μm, Waters, Manchester, UK) maintained at 60 °C. Mobile phase composition was (A) water and (B) methanol, both with 5 mmol/L ammonium formate and 0.1 % formic acid. The elution gradient began at 5 % B 0–1 min and increased linearly to 100 % B by 12 min, held at 100 % B until 14 min, then at 5 % B for a further 5 min. MS data acquisition was performed in positive and negative ionisation polarity with mass range 50–1700 in 2 GHz mode with acquisition rate at 3 spectra/second. Sample injection volume was 1 and 2 µL in negative and positive polarities, respectively.
Instrument Name:	Agilent 1290 Infinity II
Column Name:	Waters Atlantis dC18 (100 x 3mm,3um)
Column Temperature:	60
Flow Gradient:	The elution gradient began at 5 % B 0–1 min and increased linearly to 100 % B by 12 min, held at 100 % B until 14 min, then at 5 % B for a further 5 min.
Solvent A:	100% water; 0.1% formic acid; 5mM ammonium formate
Solvent B:	100% methanol; 0.1% formic acid; 5mM ammonium formate
Chromatography Type:	Reversed phase

MS:

MS ID:	MS003494
Analysis ID:	AN003750
Instrument Name:	Agilent 6550 QTOF
Instrument Type:	QTOF
MS Type:	ESI
MS Comments:	MS acquisition conditions detailed in attached Supplementary Materials. Raw data were mined using the targeted feature extraction function in Masshunter Profinder (build 10.00, Agilent) with mass targets based on chemical formulae of known/predicted phe-tyr pathway metabolites from the customised compound databases described below. A combined compound database was compiled using PCDL Manager (Agilent, build 08.00). Accurate mass retention time (AMRT) matched metabolites were present in our published AMRT database, which was generated from chemical standards using the same LC-QTOF-MS methodology employed here: phenylalanine, phenylethylamine, tyrosine, N-acetyl-tyrosine, tyramine, HPPA, HPLA and HGA. Other established phenylalanine metabolites added to the database for mining by accurate mass alone were hydroxyphenylacetic acid, phenylacetaldehyde, phenylacetamide, phenylacetic acid, phenylacetylglutamine, phenylethylamine, phenyllactic acid and phenylpyruvic acid. The remaining formulae were from non-established but theoretically possible phase 1 and 2 biotransformation products derived from phenylalanine (n=74), tyrosine (n=74), HPPA (n=67) and HPLA (n=67) predicted using the Biotransformation Mass Defects tool (Agilent), in addition to the HGA biotransformation products (n=7) previously established by our group. Feature extraction parameters were accurate mass match window ±5 ppm with addition of matched retention time (RT; window ±0.3 min) for AMRT database metabolites. Allowed ion species were: H+, Na+, and NH4+ in positive polarity, and H− and CHO2- in negative polarity. Charge state range was 1–2, and dimers were allowed. ‘Find by formula’ filters were: score >60 in at least 60 % of samples in at least one sample group. Where compounds were detected in both positive and negative ionisation, the polarity with the clearest signal was selected for further analysis. Extracted peak area intensity data were exported in .csv file format and imported into Mass Profiler Professional (MPP; build 15.1, Agilent), in which all statistical analyses were performed unless stated otherwise. In MPP, all data were log2 transformed and pareto scaled. Urine data were normalised to 24-h creatinine values. QC was performed based on compound signal intensity data from the pooled samples interspersed throughout each analytical sequence. Compounds were retained for subsequent statistical analyses if a) observed in 100 % of replicate injections for at least one sample group pool, and b) peak area coefficient of variation (CV) remained <30% across replicate injections for each sample group pool across batches 1 and 2 combined.
Ion Mode:	NEGATIVE

MS ID:	MS003495
Analysis ID:	AN003751
Instrument Name:	Agilent 6550 QTOF
Instrument Type:	QTOF
MS Type:	ESI
MS Comments:	MS acquisition conditions detailed in attached Supplementary Materials. Raw data were mined using the targeted feature extraction function in Masshunter Profinder (build 10.00, Agilent) with mass targets based on chemical formulae of known/predicted phe-tyr pathway metabolites from the customised compound databases described below. A combined compound database was compiled using PCDL Manager (Agilent, build 08.00). Accurate mass retention time (AMRT) matched metabolites were present in our published AMRT database, which was generated from chemical standards using the same LC-QTOF-MS methodology employed here: phenylalanine, phenylethylamine, tyrosine, N-acetyl-tyrosine, tyramine, HPPA, HPLA and HGA. Other established phenylalanine metabolites added to the database for mining by accurate mass alone were hydroxyphenylacetic acid, phenylacetaldehyde, phenylacetamide, phenylacetic acid, phenylacetylglutamine, phenylethylamine, phenyllactic acid and phenylpyruvic acid. The remaining formulae were from non-established but theoretically possible phase 1 and 2 biotransformation products derived from phenylalanine (n=74), tyrosine (n=74), HPPA (n=67) and HPLA (n=67) predicted using the Biotransformation Mass Defects tool (Agilent), in addition to the HGA biotransformation products (n=7) previously established by our group. Feature extraction parameters were accurate mass match window ±5 ppm with addition of matched retention time (RT; window ±0.3 min) for AMRT database metabolites. Allowed ion species were: H+, Na+, and NH4+ in positive polarity, and H− and CHO2- in negative polarity. Charge state range was 1–2, and dimers were allowed. ‘Find by formula’ filters were: score >60 in at least 60 % of samples in at least one sample group. Where compounds were detected in both positive and negative ionisation, the polarity with the clearest signal was selected for further analysis. Extracted peak area intensity data were exported in .csv file format and imported into Mass Profiler Professional (MPP; build 15.1, Agilent), in which all statistical analyses were performed unless stated otherwise. In MPP, all data were log2 transformed and pareto scaled. Urine data were normalised to 24-h creatinine values. QC was performed based on compound signal intensity data from the pooled samples interspersed throughout each analytical sequence. Compounds were retained for subsequent statistical analyses if a) observed in 100 % of replicate injections for at least one sample group pool, and b) peak area coefficient of variation (CV) remained <30% across replicate injections for each sample group pool across batches 1 and 2 combined.
Ion Mode:	POSITIVE