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.
| Study ID | ST002331 |
| Study Title | Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort |
| Study 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 |
| Last Name | Kong |
| First Name | Sek Won |
| Address | 401 Park Drive, LM5528.4 |
| sekwon.kong@childrens.harvard.edu | |
| Phone | 6179192689 |
| Submit Date | 2022-10-13 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzXML |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-04-13 |
| Release Version | 1 |
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Subject:
| Subject ID: | SU002418 |
| Subject Type: | Human |
| Subject Species: | Homo sapiens |
| Taxonomy ID: | 9606 |
