Summary of Study ST002331

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 PR001495. The data can be accessed directly via it's Project DOI: 10.21228/M8GM6Q 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.

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Study IDST002331
Study TitleComprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort
Study SummaryBackground: The human exposome is composed of diverse metabolites and small chemical compounds originated from endogenous and exogenous sources, respectively. Genetic and environmental factors influence metabolite levels while the extent of genetic contributions across metabolic pathways is not yet known. Untargeted profiling of human metabolome using high-resolution mass spectrometry (HRMS) combined with genome-wide genotyping allows comprehensive identification of genetically influenced metabolites. As such previous studies of adults discovered and replicated genotype-metabotype associations. However, these associations have not been characterized in children. Results: We conducted the largest genome by metabolome-wide association study to date of children (N=441) using 619,688 common genetic variants and 14,342 features measured by HRMS. Narrow-sense heritability (h2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h2 (>0.8) for 15.9% of features and low h2 (<0.2) for most of features (62.0%). The features with high h2 were enriched for amino acid and nucleic acid metabolism while carbohydrate and lipid concentrations showed low h2. For each feature, a metabolite quantitative trait locus (mQTL) analysis was performed to identify genetic variants that were potentially associated with plasma levels. Fifty-four associations among 29 features and 43 genetic variants were identified at a genome-wide significance threshold p < 3.5x10-12 (= 5 x 10-8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found potential candidates for novel associations including CSMD1 and a monostearyl alcohol triglyceride; CALN1 and a triglyceride; RBFOX1 and dimethylarginine. A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for ADP biosynthesis, sterol synthesis, and long-chain fatty acid transport in the gene-feature network. Conclusion: Comprehensive profiling of plasma metabolome across age groups combined with genome-wide genotyping revealed a wide range of genetic influence on diverse chemical species and metabolic pathways. The developmental trajectory of a biological system is shaped by gene-environment interaction especially in early life. Therefore, continuous efforts on generating metabolomics data in diverse human tissue types across age groups are required to understand gene-environment interaction toward healthy aging trajectories.
Institute
Boston Childrens Hospital
Last NameKong
First NameSek Won
Address401 Park Drive, LM5528.4
Emailsekwon.kong@childrens.harvard.edu
Phone6179192689
Submit Date2022-10-13
Raw Data AvailableYes
Raw Data File Type(s)mzXML
Analysis Type DetailLC-MS
Release Date2023-04-13
Release Version1
Sek Won Kong Sek Won Kong
https://dx.doi.org/10.21228/M8GM6Q
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001495
Project DOI:doi: 10.21228/M8GM6Q
Project Title:Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort
Project Summary:Background: The human exposome is composed of diverse metabolites and small chemical compounds originated from endogenous and exogenous sources, respectively. Genetic and environmental factors influence metabolite levels while the extent of genetic contributions across metabolic pathways is not yet known. Untargeted profiling of human metabolome using high-resolution mass spectrometry (HRMS) combined with genome-wide genotyping allows comprehensive identification of genetically influenced metabolites. As such previous studies of adults discovered and replicated genotype-metabotype associations. However, these associations have not been characterized in children. Results: We conducted the largest genome by metabolome-wide association study to date of children (N=441) using 619,688 common genetic variants and 14,342 features measured by HRMS. Narrow-sense heritability (h2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h2 (>0.8) for 15.9% of features and low h2 (<0.2) for most of features (62.0%). The features with high h2 were enriched for amino acid and nucleic acid metabolism while carbohydrate and lipid concentrations showed low h2. For each feature, a metabolite quantitative trait locus (mQTL) analysis was performed to identify genetic variants that were potentially associated with plasma levels. Fifty-four associations among 29 features and 43 genetic variants were identified at a genome-wide significance threshold p < 3.5x10-12 (= 5 x 10-8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found potential candidates for novel associations including CSMD1 and a monostearyl alcohol triglyceride; CALN1 and a triglyceride; RBFOX1 and dimethylarginine. A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for ADP biosynthesis, sterol synthesis, and long-chain fatty acid transport in the gene-feature network. Conclusion: Comprehensive profiling of plasma metabolome across age groups combined with genome-wide genotyping revealed a wide range of genetic influence on diverse chemical species and metabolic pathways. The developmental trajectory of a biological system is shaped by gene-environment interaction especially in early life. Therefore, continuous efforts on generating metabolomics data in diverse human tissue types across age groups are required to understand gene-environment interaction toward healthy aging trajectories.
Institute:Boston Childrens Hospital
Department:Computational Health informatics Program
Laboratory:Kong Lab
Last Name:Kong
First Name:Sek Won
Address:401 Park Drive, LM5528.4
Email:sekwon.kong@childrens.harvard.edu
Phone:6179192689
Funding Source:NIMH R01MH107205

Subject:

Subject ID:SU002418
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 Treatment
SA229785VT_181117_M338_013Control
SA229786VT_181117_M338_014Control
SA229787VT_181028_M338_074Control
SA229788VT_181028_M338_073Control
SA229789VT_181202_M338_146Control
SA229790VT_181120_M338_109Control
SA229791VT_181028_M338_193Control
SA229792VT_181110_M338_224Control
SA229793VT_181117_M338_151Control
SA229794VT_181110_M338_223Control
SA229795VT_181028_M338_194Control
SA229796VT_181202_M338_145Control
SA229797VT_181120_M338_110Control
SA229798VT_181119_M338_103Control
SA229799VT_181013_M338_193Control
SA229800VT_181013_M338_194Control
SA229801VT_181202_M338_176Control
SA229802VT_181202_M338_175Control
SA229803VT_181106_M338_230Control
SA229804VT_181116_M338_061Control
SA229805VT_181116_M338_062Control
SA229806VT_181031_M338_212Control
SA229807VT_181117_M338_152Control
SA229808VT_181031_M338_211Control
SA229809VT_181022_M338_248Control
SA229810VT_181022_M338_247Control
SA229811VT_181119_M338_104Control
SA229812VT_181013_M338_164Control
SA229813VT_181127_M338_235Control
SA229814VT_181127_M338_236Control
SA229815VT_181124_M338_080Control
SA229816VT_181124_M338_079Control
SA229817VT_181016_M338_056Control
SA229818VT_181212_M338_247Control
SA229819VT_181212_M338_248Control
SA229820VT_181119_M338_140Control
SA229821VT_181123_M338_175Control
SA229822VT_181119_M338_139Control
SA229823VT_181214_M338_116Control
SA229824VT_181214_M338_115Control
SA229825VT_181016_M338_055Control
SA229826VT_181021_M338_230Control
SA229827VT_181101_M338_085Control
SA229828VT_181101_M338_086Control
SA229829VT_181203_M338_152Control
SA229830VT_181203_M338_151Control
SA229831VT_181106_M338_229Control
SA229832VT_181130_M338_205Control
SA229833VT_181130_M338_206Control
SA229834VT_181030_M338_164Control
SA229835VT_181021_M338_229Control
SA229836VT_181030_M338_163Control
SA229837VT_181119_M338_014Control
SA229838VT_181119_M338_013Control
SA229839VT_181013_M338_163Control
SA229840VT_181026_M338_194Control
SA229841VT_181012_M338_044Control
SA229842VT_181012_M338_067Control
SA229843VT_181012_M338_043Control
SA229844VT_181209_M338_146Control
SA229845VT_181209_M338_145Control
SA229846VT_181012_M338_068Control
SA229847VT_181122_M338_037Control
SA229848VT_181211_M338_199Control
SA229849VT_181211_M338_200Control
SA229850VT_181028_M338_206Control
SA229851VT_181028_M338_205Control
SA229852VT_181122_M338_038Control
SA229853VT_181121_M338_092Control
SA229854VT_181121_M338_091Control
SA229855VT_181011_M338_038Control
SA229856VT_181031_M338_151Control
SA229857VT_181011_M338_037Control
SA229858VT_181209_M338_194Control
SA229859VT_181209_M338_193Control
SA229860VT_181031_M338_152Control
SA229861VT_181106_M338_037Control
SA229862VT_181108_M338_181Control
SA229863VT_181108_M338_182Control
SA229864VT_181120_M338_080Control
SA229865VT_181120_M338_079Control
SA229866VT_181106_M338_038Control
SA229867VT_181124_M338_217Control
SA229868VT_181124_M338_218Control
SA229869VT_181209_M338_079Control
SA229870VT_181209_M338_080Control
SA229871VT_181113_M338_194Control
SA229872VT_181113_M338_193Control
SA229873VT_181111_M338_230Control
SA229874VT_181103_M338_013Control
SA229875VT_181103_M338_014Control
SA229876VT_181116_M338_146Control
SA229877VT_181026_M338_193Control
SA229878VT_181116_M338_145Control
SA229879VT_181119_M338_110Control
SA229880VT_181119_M338_109Control
SA229881VT_181111_M338_229Control
SA229882VT_181210_M338_056Control
SA229883VT_181106_M338_056Control
SA229884VT_181123_M338_211Control
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Collection:

Collection ID:CO002411
Collection Summary:Individuals were enrolled in the PrecisionLink Biobank for Health Discovery at Boston Children’s Hospital (BCH) from January 2016 to November 2019. We collected 441 plasma samples from 230 females and 211 males with mean ages 15.7 and 14.3 years old, respectively (ranges from 4.8 months to 60.1 years). The International Classification of Diseases (versions 9 and 10) and SNOMED CT codes were collected for participants from the BCH Cerner electric health record database. To comply with the Health Insurance Portability and Accountability Act rules for protected health information, medical record identifier and personal information were removed from the EHR extracts and universal unique identifiers (UUIDs) were assigned to everyone. All analyses were performed with UUIDs, age at blood collection, gender information, and sample identifiers for plasma and DNA samples, which were provided by the BCH Biobank. The study was reviewed and approved by the BCH Institutional Review Board.
Sample Type:Blood (plasma)

Treatment:

Treatment ID:TR002430
Treatment Summary:Plasma samples in 50μL aliquot were mixed with acetonitrile containing 14 stable isotope internal standards at a 2:1 ratio to precipitate proteins. Samples were then equilibrated on ice for 30 minutes and centrifuged for 10 minutes at 13,400 rpm at 4°C. The supernatant was transferred to autosampler vials and kept in a refrigerated autosampler until analysis. Each extract was analyzed in triplicate using a dual column chromatography scheme that includes hydrophilic interaction liquid chromatography (HILIC; XBridge BEH Amide XP HILIC column; Waters, Waltham, MA, 50x2.1mm, 2.5μm) and reversed phase liquid chromatography (RPLC; C18 column; Higgins Analytical, Mountain View, CA, 50x2.1mm, 2.6 μm).

Sample Preparation:

Sampleprep ID:SP002424
Sampleprep Summary:Samples are prepared for metabolomics analysis using established methods (Johnson et al. (2010). Analyst; Go et al. (2015). Tox Sci). Prior to analysis, plasma aliquots were removed from storage at -80°C and thawed on ice. Each cryotube is then vortexed briefly to ensure homogeneity, and 50 μL transferred to a clean microfuge tube. Immediately after, the plasma is treated with 100 μL of ice-cold LC-MS grade acetonitrile (Sigma Aldrich) containing 2.5 μL of internal standard solution with eight stable isotopic chemicals selected to cover a range of chemical properties. Following addition of acetonitrile, plasma is then equilibrated for 30 min on ice, upon which precipitated proteins are removed by centrifuge (16.1 ×g at 4°C for 10 min). The resulting supernatant (100 μL) is removed, added to a low volume autosampler vial and maintained at 4°C until analysis (<22 h).
Sampleprep Protocol Filename:EmoryUniversity_HRM_sample_preparation_082016_01.pdf

Combined analysis:

Analysis ID AN003804 AN003805
Analysis type MS MS
Chromatography type HILIC Reversed phase
Chromatography system Dionex UltiMate 3000 Dionex UltiMate 3000
Column Waters XBridge BEH Amide XP HILIC (50 x 2.1mm,2.5um) Product #186006089; Thermo Accucore HILIC guard with holder,Product # 17526-012105 Higgins endcapped C18 stainless steel (50 x 2.1mm,3um),Product #TS-0521-C183; Thermo Accucore C18 guard with holder,Product #17126-014005
MS Type ESI ESI
MS instrument type Orbitrap Orbitrap
MS instrument name Thermo Q Exactive HF hybrid orbitrap Thermo Q Exactive HF hybrid orbitrap
Ion Mode POSITIVE NEGATIVE
Units peak area peak area

Chromatography:

Chromatography ID:CH002814
Chromatography Summary:The HILIC column is operated parallel to reverse phase column for simultaneous analytical separation and column flushing through the use of a dual head HPLC pump equipped with 10- port and 6-port switching valves. During operation of HILIC separation method, the MS is operated in positive ion mode and 10 μL of sample is injected onto the HILIC column while the reverse phase column is flushing with wash solution. Flow rate is maintained at 0.35 mL/min until 1.5 min, increased to 0.4 mL/min at 4 min and held for 1 min. Solvent A is 100% LC-MS grade water, solvent B is 100% LC-MS grade acetonitrile and solvent C is 2% formic acid (v/v) in LC-MS grade water. Initial mobile phase conditions are 22.5% A, 75% B, 2.5% C hold for 1.5 min, with linear gradient to 77.5% A, 20% B, 2.5% C at 4 min, hold for 1 min, resulting in a total analytical run time of 5 min. During the flushing phase (reverse phase analytical separation), the HILIC column is equilibrated with a wash solution of 77.5% A, 20% B, 2.5% C.
Methods Filename:EmoryUniversity_HRM_QEHF_chromatography_5min_092017_v1.pdf
Instrument Name:Dionex UltiMate 3000
Column Name:Waters XBridge BEH Amide XP HILIC (50 x 2.1mm,2.5um) Product #186006089; Thermo Accucore HILIC guard with holder,Product # 17526-012105
Column Temperature:60
Solvent A:100% water
Solvent B:100% acetonitrile
Chromatography Type:HILIC
  
Chromatography ID:CH002815
Chromatography Summary:The C18 column is operated parallel to the HILIC column for simultaneous analytical separation and column flushing through the use of a dual head HPLC pump equipped with 10-port and 6- port switching valves. During operation of the C18 method, the MS is operated in negative ion mode and 10 μL of sample is injected onto the C18 column while the HILIC column is flushing with wash solution. Flow rate is maintained at 0.4 mL/min until 1.5 min, increased to 0.5 mL/min at 2 min and held for 3 min. Solvent A is 100% LC-MS grade water, solvent B is 100% LC-MS grade acetonitrile and solvent C is 10mM ammonium acetate in LC-MS grade water. Initial mobile phase conditions are 60% A, 35% B, 5% C hold for 0.5 min, with linear gradient to 0% A, 95% B, 5% C at 1.5 min, hold for 3.5 min, resulting in a total analytical run time of 5 min. During the flushing phase (HILIC analytical separation), the C18 column is equilibrated with a wash solution of 0% A, 95% B, 5% C until 2.5 min, followed by an equilibration solution of 60% A, 35% B, 5% C for 2.5 min.
Instrument Name:Dionex UltiMate 3000
Column Name:Higgins endcapped C18 stainless steel (50 x 2.1mm,3um),Product #TS-0521-C183; Thermo Accucore C18 guard with holder,Product #17126-014005
Column Temperature:60
Solvent A:100% water
Solvent B:100% acetonitrile
Chromatography Type:Reversed phase

MS:

MS ID:MS003546
Analysis ID:AN003804
Instrument Name:Thermo Q Exactive HF hybrid orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:no comment
Ion Mode:POSITIVE
Processing Parameters File:EmoryUniversity_HRM_DataAnalysis_MS_092017_v1.pdf
Analysis Protocol File:EmoryUniversity_HRM_QEHF_MassSpec_092017_v1.pdf
  
MS ID:MS003547
Analysis ID:AN003805
Instrument Name:Thermo Q Exactive HF hybrid orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:no comment
Ion Mode:NEGATIVE
Processing Parameters File:EmoryUniversity_HRM_DataAnalysis_MS_092017_v1.pdf
Analysis Protocol File:EmoryUniversity_HRM_QEHF_MassSpec_092017_v1.pdf
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