Summary of Study ST002296

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 PR001471. The data can be accessed directly via it's Project DOI: 10.21228/M8KH70 This work is supported by NIH grant, U2C- DK119886.

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Study IDST002296
Study TitleComprehensive biotransformation analysis of phenylalanine-tyrosine metabolism reveals alternative routes of metabolite clearance in nitisinone-treated alkaptonuria (Serum metabolomic analysis)
Study TypeSerum metabolomic analysis (study 1 of 2)
Study SummaryBackground: Metabolomic analyses in alkaptonuria (AKU) have recently revealed alternative pathways in phenylalanine-tyrosine (phe-tyr) metabolism from biotransformation of homo-gentisic acid (HGA), the active molecule in this disease. The aim of this research was to study the phe-tyr metabolic pathway and whether the metabolites upstream of HGA, increased in nitisinone-treated patients, also undergo phase 1 and 2 biotransformation reactions. Methods: Metabolomic analyses were performed on serum and urine from patients partaking in the SONIA 2 phase 3 international randomised-controlled trial of nitisinone in AKU (EudraCT no. 2013-001633-41). Serum and urine samples were taken from the same patients at baseline (pre-nitisinone) then at 24 and 48 months on nitisinone treatment (patients N = 47 serum; 53 urine) or no treatment (patients N = 45 serum; 50 urine). Targeted feature extraction was per-formed to specifically mine data for the entire complement of theoretically predicted phase 1 and 2 biotransformation products derived from phenylalanine, tyrosine, 4-hydroxyphenylpyruvic acid and 4-hydroxyphenyllactic acid, in addition to phenylalanine-derived metabolites with known increases in phenylketonuria. Results: In total, we ob-served 13 phase 1 and 2 biotransformation products from phenylalanine through to HGA. Each of these products were observed in urine and two were detected in serum. The derivatives of the metabolites upstream of HGA were markedly increased in urine of nitisinone-treated patients (fold change 1.2-16.2) and increases in 12 of these compounds were directly proportional to the degree of nitisinone-induced hypertyrosinaemia (correlation coefficient with serum tyrosine = 0.2-0.7). Increases in the urinary phenylalanine metabolites were also observed across consecutive visits in the treated group. Conclusions: Nitisinone treatment results in marked increases in a wider network of phe-tyr metabolites than shown before. This network comprises alternative biotransformation products from the major metabolites of this pathway, produced by reactions including hydration (phase 1) and bioconjugation (phase 2) of acetyl, methyl, acetylcysteine, glucuronide, glycine and sulfate groups. We propose that these alternative routes of phe-tyr metabolism, predominantly in urine, minimise tyrosinaemia as well as phenylalanaemia.
Institute
University of Liverpool Institute of Life Course & Medical Sciences
DepartmentDepartment of Musculoskeletal & Ageing Science
Last NameBrendan
First NameNorman
AddressWilliam Henry Duncan Building, 6 West Derby Street, Liverpool, UK. L7 8TX
Emailbnorman@liverpool.ac.uk
Phone+447809606497
Submit Date2022-09-26
Num Groups2
Total Subjects92
Num Males59
Num Females33
Raw Data AvailableYes
Raw Data File Type(s)d
Analysis Type DetailLC-MS
Release Date2022-10-14
Release Version1
Norman Brendan Norman Brendan
https://dx.doi.org/10.21228/M8KH70
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001471
Project DOI:doi: 10.21228/M8KH70
Project Title:Metabolomic analysis in SONIA 2, a phase 3 international randomised-controlled trial of nitisinone in alkaptonuria (AKU)
Project Summary:Abstract from main SONIA 2 publication: Background Alkaptonuria is a rare, genetic, multisystem disease characterised by the accumulation of homogentisic acid (HGA). No HGA-lowering therapy has been approved to date. The aim of SONIA 2 was to investigate the efficacy and safety of once-daily nitisinone for reducing HGA excretion in patients with alkaptonuria and to evaluate whether nitisinone has a clinical benefit. Methods SONIA 2 was a 4-year, open-label, evaluator-blind, randomised, no treatment controlled, parallel-group study done at three sites in the UK, France, and Slovakia. Patients aged 25 years or older with confirmed alkaptonuria and any clinical disease manifestations were randomly assigned (1:1) to receive either oral nitisinone 10 mg daily or no treatment. Patients could not be masked to treatment due to colour changes in the urine, but the study was evaluator-blinded as far as possible. The primary endpoint was daily urinary HGA excretion (u-HGA24) after 12 months. Clinical evaluation Alkaptonuria Severity Score Index (cAKUSSI) score was assessed at 12, 24, 36, and 48 months. Efficacy variables were analysed in all randomly assigned patients with a valid u-HGA24 measurement at baseline. Safety variables were analysed in all randomly assigned patients. The study was registered at ClinicalTrials.gov (NCT01916382). Findings Between May 7, 2014, and Feb 16, 2015, 139 patients were screened, of whom 138 were included in the study, with 69 patients randomly assigned to each group. 55 patients in the nitisinone group and 53 in the control group completed the study. u-HGA24 at 12 months was significantly decreased by 99·7% in the nitisinone group compared with the control group (adjusted geometric mean ratio of nitisinone/control 0·003 [95% CI 0·003 to 0·004], p<0·0001). At 48 months, the increase in cAKUSSI score from baseline was significantly lower in the nitisinone group compared with the control group (adjusted mean difference –8·6 points [–16·0 to –1·2], p=0·023). 400 adverse events occurred in 59 (86%) patients in the nitisinone group and 284 events occurred in 57 (83%) patients in the control group. No treatment-related deaths occurred. Interpretation Nitisinone 10 mg daily was well tolerated and effective in reducing urinary excretion of HGA. Nitisinone decreased ochronosis and improved clinical signs, indicating a slower disease progression.
Institute:University of Liverpool Institute of Life Course & Medical Sciences
Department:Department of Musculoskeletal & Ageing Science
Last Name:Brendan
First Name:Norman
Address:William Henry Duncan Building, 6 West Derby Street, Liverpool, UK. L7 8TX
Email:bnorman@liverpool.ac.uk
Phone:+447809606497
Funding Source:European Commission for the Framework 7 grant award (DevelopAKUre, project number: 304985), Alkaptonuria Society (BPN is funded by the Alkaptonuria Society through a Sireau Fellowship Award).

Subject:

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

Factors:

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

mb_sample_id local_sample_id Trial arm
SA220373P40_V4Treated
SA220374P40_V1Treated
SA220375P39_V6Treated
SA220376P40_V6Treated
SA220377L35_V4Treated
SA220378L33_V6Treated
SA220379L35_V1Treated
SA220380P39_V4Treated
SA220381L35_V6Treated
SA220382P36_V6Treated
SA220383L6_V1Treated
SA220384L6_V4Treated
SA220385L6_V6Treated
SA220386L40_V6Treated
SA220387L40_V4Treated
SA220388L33_V4Treated
SA220389P36_V4Treated
SA220390L40_V1Treated
SA220391P39_V1Treated
SA220392L30_V6Treated
SA220393P46_V1Treated
SA220394P44_V6Treated
SA220395P44_V4Treated
SA220396P46_V4Treated
SA220397P46_V6Treated
SA220398P47_V6Treated
SA220399P47_V4Treated
SA220400P47_V1Treated
SA220401L28_V1Treated
SA220402P26_V4Treated
SA220403L30_V1Treated
SA220404L30_V4Treated
SA220405L7_V1Treated
SA220406P43_V1Treated
SA220407P43_V4Treated
SA220408L28_V6Treated
SA220409P44_V1Treated
SA220410P43_V6Treated
SA220411L33_V1Treated
SA220412L7_V6Treated
SA220413P30_V4Treated
SA220414P30_V1Treated
SA220415P3_V6Treated
SA220416P2_V6Treated
SA220417P2_V4Treated
SA220418P18_V4Treated
SA220419P18_V6Treated
SA220420P2_V1Treated
SA220421P3_V4Treated
SA220422P3_V1Treated
SA220423P23_V6Treated
SA220424P26_V6Treated
SA220425P26_V1Treated
SA220426P23_V4Treated
SA220427P23_V1Treated
SA220428P22_V1Treated
SA220429P22_V4Treated
SA220430P22_V6Treated
SA220431P18_V1Treated
SA220432P30_V6Treated
SA220433F1_V1Treated
SA220434P34_V6Treated
SA220435P11_V1Treated
SA220436P36_V1Treated
SA220437L8_V6Treated
SA220438P48_V1Treated
SA220439L8_V1Treated
SA220440L8_V4Treated
SA220441P11_V4Treated
SA220442P11_V6Treated
SA220443P31_V6Treated
SA220444P31_V4Treated
SA220445P31_V1Treated
SA220446P15_V6Treated
SA220447P15_V4Treated
SA220448P34_V4Treated
SA220449P34_V1Treated
SA220450P15_V1Treated
SA220451L7_V4Treated
SA220452L28_V4Treated
SA220453F29_V6Treated
SA220454P55_V6Treated
SA220455L19_V6Treated
SA220456F29_V4Treated
SA220457F29_V1Treated
SA220458F26_V1Treated
SA220459F26_V4Treated
SA220460F26_V6Treated
SA220461F31_V1Treated
SA220462F31_V4Treated
SA220463F5_V4Treated
SA220464F5_V6Treated
SA220465P55_V1Treated
SA220466F5_V1Treated
SA220467F4_V6Treated
SA220468F31_V6Treated
SA220469F4_V1Treated
SA220470F4_V4Treated
SA220471F24_V6Treated
SA220472F24_V4Treated
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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.

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
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