Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort
Abstract 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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-12-01
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| Series: | Human Genomics |
| Online Access: | https://doi.org/10.1186/s40246-022-00440-w |
| _version_ | 1828092592562110464 |
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| author | In-Hee Lee Matthew Ryan Smith Azam Yazdani Sumiti Sandhu Douglas I. Walker Kenneth D. Mandl Dean P. Jones Sek Won Kong |
| author_facet | In-Hee Lee Matthew Ryan Smith Azam Yazdani Sumiti Sandhu Douglas I. Walker Kenneth D. Mandl Dean P. Jones Sek Won Kong |
| author_sort | In-Hee Lee |
| collection | DOAJ |
| description | Abstract 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 (h 2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h 2 (> 0.8) for 15.9% of features and low h 2 (< 0.2) for most of features (62.0%). The features with high h 2 were enriched for amino acid and nucleic acid metabolism, while carbohydrate and lipid concentrations showed low h 2. For each feature, a metabolite quantitative trait loci (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 < 3.5 × 10–12 (= 5 × 10–8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; and ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found potential candidates for novel associations including CSMD1 and a monostearyl alcohol triglyceride (m/z 781.7483, retention time (RT) 89.3 s); CALN1 and Tridecanol (m/z 283.2741, RT 27.6). A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for dADP 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. |
| first_indexed | 2024-04-11T06:30:02Z |
| format | Article |
| id | doaj.art-e53b8a652d42422ca398f6c06db3d480 |
| institution | Directory Open Access Journal |
| issn | 1479-7364 |
| language | English |
| last_indexed | 2024-04-11T06:30:02Z |
| publishDate | 2022-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Human Genomics |
| spelling | doaj.art-e53b8a652d42422ca398f6c06db3d4802022-12-22T04:40:08ZengBMCHuman Genomics1479-73642022-12-0116111410.1186/s40246-022-00440-wComprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohortIn-Hee Lee0Matthew Ryan Smith1Azam Yazdani2Sumiti Sandhu3Douglas I. Walker4Kenneth D. Mandl5Dean P. Jones6Sek Won Kong7Computational Health Informatics Program, Boston Children’s HospitalDivision of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Emory UniversityCenter of Perioperative Genetics and Genomics, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Harvard Medical SchoolComputational Health Informatics Program, Boston Children’s HospitalDepartment of Environmental Medicine and Public Health, Icahn School of Medicine at Mount SinaiComputational Health Informatics Program, Boston Children’s HospitalDivision of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Emory UniversityComputational Health Informatics Program, Boston Children’s HospitalAbstract 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 (h 2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h 2 (> 0.8) for 15.9% of features and low h 2 (< 0.2) for most of features (62.0%). The features with high h 2 were enriched for amino acid and nucleic acid metabolism, while carbohydrate and lipid concentrations showed low h 2. For each feature, a metabolite quantitative trait loci (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 < 3.5 × 10–12 (= 5 × 10–8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; and ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found potential candidates for novel associations including CSMD1 and a monostearyl alcohol triglyceride (m/z 781.7483, retention time (RT) 89.3 s); CALN1 and Tridecanol (m/z 283.2741, RT 27.6). A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for dADP 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.https://doi.org/10.1186/s40246-022-00440-w |
| spellingShingle | In-Hee Lee Matthew Ryan Smith Azam Yazdani Sumiti Sandhu Douglas I. Walker Kenneth D. Mandl Dean P. Jones Sek Won Kong Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort Human Genomics |
| title | Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort |
| title_full | Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort |
| title_fullStr | Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort |
| title_full_unstemmed | Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort |
| title_short | Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort |
| title_sort | comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort |
| url | https://doi.org/10.1186/s40246-022-00440-w |
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