Summary of Study ST001402

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 PR000962. The data can be accessed directly via it's Project DOI: 10.21228/M8BM3B This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

Study ID	ST001402
Study Title	Ontogeny related changes in the pediatric liver metabolome
Study Summary	A major challenge in implementing personalized medicine in pediatrics is identifying appropriate drug dosages for children. The majority of drug dosing studies have been based on adult populations, often with modification of the dosing for children based on size and weight. However, the growth and development experienced by children between birth and adulthood represents a dynamically changing biological system, with implications for effective drug dosing, efficacy as well as potential drug toxicity. The purpose of this study was to apply a metabolomics approach to gain preliminary insights into the ontogeny of liver function from newborn to adolescent.
Institute	Moffitt Cancer Center
Last Name	Fridley
First Name	Brooke
Address	12902 USF Magnolia Drive
Email	brooke.fridley@moffitt.org
Phone	813-745-1461
Submit Date	2020-05-27
Analysis Type Detail	LC-MS
Release Date	2020-09-10
Release Version	1

Select appropriate tab below to view additional metadata details:

Project:

Project ID:	PR000962
Project DOI:	doi: 10.21228/M8BM3B
Project Title:	Ontogeny related changes in the pediatric liver metabolome
Project Summary:	A major challenge in implementing personalized medicine in pediatrics is identifying appropriate drug dosages for children. The majority of drug dosing studies have been based on adult populations, often with modification of the dosing for children based on size and weight. However, the growth and development experienced by children between birth and adulthood represents a dynamically changing biological system, with implications for effective drug dosing, efficacy as well as potential drug toxicity. The purpose of this study was to apply a metabolomics approach to gain preliminary insights into the ontogeny of liver function from newborn to adolescent.
Institute:	Moffitt Cancer Center
Last Name:	Fridley
First Name:	Brooke
Address:	12902 USF Magnolia Dr
Email:	brooke.fridley@moffitt.org
Phone:	813-745-1461

Subject:

Subject ID:	SU001476
Subject Type:	Human
Subject Species:	Homo sapiens
Taxonomy ID:	9606
Age Or Age Range:	0-18 years old
Gender:	Male and female

Factors:

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

mb_sample_id	local_sample_id	GROUP_DESCRIPTION
SA113927	CMH70994	12 to 18 years
SA113928	CMH8910	12 to 18 years
SA113929	CMH8906	12 to 18 years
SA113930	CMH885	12 to 18 years
SA113931	CMH8935	12 to 18 years
SA113932	CMH9027	12 to 18 years
SA113933	CMH9127	12 to 18 years
SA113934	CMH71281	12 to 18 years
SA113935	CMH64	12 to 18 years
SA113936	CMH9032	12 to 18 years
SA113913	CMH9011	1 to 5.99 years
SA113914	CMH8926	1 to 5.99 years
SA113915	CMH689	1 to 5.99 years
SA113916	CMH9023	1 to 5.99 years
SA113917	CMH792	1 to 5.99 years
SA113918	CMH9101	1 to 5.99 years
SA113919	CMH9612	1 to 5.99 years
SA113920	CMH9609	1 to 5.99 years
SA113921	CMH9608	1 to 5.99 years
SA113922	CMH677	1 to 5.99 years
SA113923	CMH9036	1 to 5.99 years
SA113924	CMH872	1 to 5.99 years
SA113925	CMH346	1 to 5.99 years
SA113926	CMH617	1 to 5.99 years
SA113937	CMH9003	6 to 11.99 years
SA113938	CMH9611	6 to 11.99 years
SA113939	CMH1860	6 to 11.99 years
SA113940	CMH8925	6 to 11.99 years
SA113941	CMH9013	6 to 11.99 years
SA113942	CMH9006	6 to 11.99 years
SA113943	CMH8920	6 to 11.99 years
SA113944	CMH70898	6 to 11.99 years
SA113945	CMH71000	6 to 11.99 years
SA113946	CMH8902	6 to 11.99 years
SA113947	CMH8917	6 to 11.99 years
SA113948	CMH1325	< 1 year of age
SA113949	CMH1296	< 1 year of age
SA113950	CMH1281	< 1 year of age
SA113951	CMH1157	< 1 year of age
SA113952	CMH1547	< 1 year of age
SA113953	CMH774	< 1 year of age
SA113954	CMH435	< 1 year of age
SA113955	CMH1055	< 1 year of age
SA113956	CMH86	< 1 year of age
SA113957	CMH825	< 1 year of age
SA113958	CMH569	< 1 year of age
SA113959	CMH780	< 1 year of age
SA113960	CMH759	< 1 year of age

Showing results 1 to 48 of 48

Showing results 1 to 48 of 48

Collection:

Collection ID:	CO001471
Collection Summary:	Postmortem pediatric human liver tissue samples were obtained through the Brain and Tissue Bank for Developmental Disorders at the University of Maryland (Baltimore, MD), the Liver Tissue Cell Distribution System (LTCDS; University of Pittsburgh and University of Minnesota), and XenoTech LLC (Lenexa, KS). The use of these tissues was classified as nonhuman subject research by the Children's Mercy Hospital Pediatric Institutional Review Board A replication set of post-mortem liver tissue samples from autopsy of fetuses (from therapeutic abortions or stillbirths) and infants was provided by the Erasmus Medical Center Tissue Bank, Sophia Children’s Hospital, Rotterdam, The Netherlands. Tissue was procured at the time of autopsy within 24 h after death and snap-frozen at −80 °C for later research use. The Erasmus Medical Center Research Ethics Board waived the need for formal ethics approval according to the Dutch Law on Medical Research in Humans. Tissue was collected when parental written informed consent for both autopsy and the explicit use of the tissue for research was present. Samples were selected based on the absence of a clinical diagnosis or medications affecting the liver (CMH and Erasmus), and tissue that was histologically normal (Erasmus). Samples were stratified into four age groups: less than one year of age (age group 1), one to less than six years (age group 2), six to less than 12 years (age group 3), and 12 to 18 years of age (age group 4). In total 98 liver samples were available for metabolomic analysis.
Sample Type:	Liver

Treatment:

Treatment ID:	TR001491
Treatment Summary:	No treatment.

Sample Preparation:

Sampleprep ID:	SP001484
Sampleprep Summary:	Experiment 1 The first experiment was completed using the first set of samples (N = 48) (referred to as “batch 1”). Metabolite extraction and detection were performed at Metabolon Inc. (Durham, NC, USA) as previously described (Evans et al., 2009). Briefly, liver samples were extracted through the automated MicroLab STAR® system (Hamilton Company, UT, USA), centrifuged, and the resulting supernatants were analyzed by UPLC-MS/MS in a positive and negative ion mode (UPLC: Waters, Milford, MA; mass spectrometer: Thermo-Finnigan LTQ, Thermo Fisher Scientific, Waltham, MA, scan range, 80–1000 m/z) and by GC-MS (Thermo-Finnigan Trace DSQ fast-scanning single-quadrupole mass spectrometer, scan range 50–750 m/z). The final experiment 1 metabolomic dataset comprised a total of 751 biochemicals, 478 scompounds of known identity (named biochemicals) and 273 compounds of unknown structural identity. As initial statistical analysis revealed an age-dependent effect that could not be distinguished from a tissue source-related effect, a replication set of group 1 samples was obtained through collaboration with Erasmus Medical Center/Sophia Children’s Hospital. Experiment 2 Given that the metabolomic platform changed between the first analysis and the sample set containing the replication samples, the second experiment examined the entire set of 98 samples. The same 48 samples previously processed in Experiment 1 and designated as “batch 1” above were re-analyzed on the new platform, with the results designated “batch 2”. The replication samples from Erasmus/Sophia Children’s Hospital and additional samples from CMH (N=50) are designated as “batch 3”. Following the sample extraction, the resulting extract was analyzed using a Waters ACQUITY ultra-performance liquid chromatography (UPLC) and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution (Evans et al., 2014). Four methods were utilized: two separate reverse phase (RP)/UPLC-MS/MS methods with positive ion mode electrospray ionization (ESI), RP/UPLC-MS/MS with negative ion mode ESI, and HILIC/UPLC-MS/MS with negative ion mode ESI. The MS analysis alternated between MS and data-dependent MSn scans using dynamic exclusion. The scan range varied slighted between methods but covered 70-1000 m/z. The final experiment 2 metabolomic dataset comprised a total of 971 biochemicals, 779 compounds of known identity (named biochemicals) and 192 compounds of unknown structural identity.

Sampleprep ID:

SP001484

Sampleprep Summary:

Experiment 1 The first experiment was completed using the first set of samples (N = 48) (referred to as “batch 1”). Metabolite extraction and detection were performed at Metabolon Inc. (Durham, NC, USA) as previously described (Evans et al., 2009). Briefly, liver samples were extracted through the automated MicroLab STAR® system (Hamilton Company, UT, USA), centrifuged, and the resulting supernatants were analyzed by UPLC-MS/MS in a positive and negative ion mode (UPLC: Waters, Milford, MA; mass spectrometer: Thermo-Finnigan LTQ, Thermo Fisher Scientific, Waltham, MA, scan range, 80–1000 m/z) and by GC-MS (Thermo-Finnigan Trace DSQ fast-scanning single-quadrupole mass spectrometer, scan range 50–750 m/z). The final experiment 1 metabolomic dataset comprised a total of 751 biochemicals, 478 scompounds of known identity (named biochemicals) and 273 compounds of unknown structural identity. As initial statistical analysis revealed an age-dependent effect that could not be distinguished from a tissue source-related effect, a replication set of group 1 samples was obtained through collaboration with Erasmus Medical Center/Sophia Children’s Hospital. Experiment 2 Given that the metabolomic platform changed between the first analysis and the sample set containing the replication samples, the second experiment examined the entire set of 98 samples. The same 48 samples previously processed in Experiment 1 and designated as “batch 1” above were re-analyzed on the new platform, with the results designated “batch 2”. The replication samples from Erasmus/Sophia Children’s Hospital and additional samples from CMH (N=50) are designated as “batch 3”. Following the sample extraction, the resulting extract was analyzed using a Waters ACQUITY ultra-performance liquid chromatography (UPLC) and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution (Evans et al., 2014). Four methods were utilized: two separate reverse phase (RP)/UPLC-MS/MS methods with positive ion mode electrospray ionization (ESI), RP/UPLC-MS/MS with negative ion mode ESI, and HILIC/UPLC-MS/MS with negative ion mode ESI. The MS analysis alternated between MS and data-dependent MSn scans using dynamic exclusion. The scan range varied slighted between methods but covered 70-1000 m/z. The final experiment 2 metabolomic dataset comprised a total of 971 biochemicals, 779 compounds of known identity (named biochemicals) and 192 compounds of unknown structural identity.

Combined analysis:

Analysis ID	AN002344
Analysis type	MS
Chromatography type	Reversed phase
Chromatography system	Thermo Trace 1310
Column	Waters Acquity BEH C8 (100 x 2.1mm,1.7um)
MS Type	ESI
MS instrument type	Single quadrupole
MS instrument name	Thermo Trace DSQ
Ion Mode	UNSPECIFIED
Units	estimated abundances

Chromatography:

Chromatography ID:	CH001717
Instrument Name:	Thermo Trace 1310
Column Name:	Waters Acquity BEH C8 (100 x 2.1mm,1.7um)
Chromatography Type:	Reversed phase

MS:

MS ID:	MS002186
Analysis ID:	AN002344
Instrument Name:	Thermo Trace DSQ
Instrument Type:	Single quadrupole
MS Type:	ESI
MS Comments:	Metabolon
Ion Mode:	UNSPECIFIED