Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses.
Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitat...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2015-01-01
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| Series: | PLoS Genetics |
| Online Access: | https://doi.org/10.1371/journal.pgen.1004835 |
| _version_ | 1828266314136813568 |
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| author | Ayşe Demirkan Peter Henneman Aswin Verhoeven Harish Dharuri Najaf Amin Jan Bert van Klinken Lennart C Karssen Boukje de Vries Axel Meissner Sibel Göraler Arn M J M van den Maagdenberg André M Deelder Peter A C 't Hoen Cornelia M van Duijn Ko Willems van Dijk |
| author_facet | Ayşe Demirkan Peter Henneman Aswin Verhoeven Harish Dharuri Najaf Amin Jan Bert van Klinken Lennart C Karssen Boukje de Vries Axel Meissner Sibel Göraler Arn M J M van den Maagdenberg André M Deelder Peter A C 't Hoen Cornelia M van Duijn Ko Willems van Dijk |
| author_sort | Ayşe Demirkan |
| collection | DOAJ |
| description | Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value = 1.27×10-32), PRODH with proline (P-value = 1.11×10-19), SLC16A9 with carnitine level (P-value = 4.81×10-14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value = 1.65×10-19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value = 1.26×10-8), KCNJ16 with 3-hydroxybutyrate (P-value = 1.65×10-8) and 2p12 locus with valine (P-value = 3.49×10-8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits. |
| first_indexed | 2024-04-13T04:51:00Z |
| format | Article |
| id | doaj.art-bc9c29efd0e144fa96cfeee07c156383 |
| institution | Directory Open Access Journal |
| issn | 1553-7390 1553-7404 |
| language | English |
| last_indexed | 2024-04-13T04:51:00Z |
| publishDate | 2015-01-01 |
| publisher | Public Library of Science (PLoS) |
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| series | PLoS Genetics |
| spelling | doaj.art-bc9c29efd0e144fa96cfeee07c1563832022-12-22T03:01:41ZengPublic Library of Science (PLoS)PLoS Genetics1553-73901553-74042015-01-01111e100483510.1371/journal.pgen.1004835Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses.Ayşe DemirkanPeter HennemanAswin VerhoevenHarish DharuriNajaf AminJan Bert van KlinkenLennart C KarssenBoukje de VriesAxel MeissnerSibel GöralerArn M J M van den MaagdenbergAndré M DeelderPeter A C 't HoenCornelia M van DuijnKo Willems van DijkMetabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value = 1.27×10-32), PRODH with proline (P-value = 1.11×10-19), SLC16A9 with carnitine level (P-value = 4.81×10-14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value = 1.65×10-19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value = 1.26×10-8), KCNJ16 with 3-hydroxybutyrate (P-value = 1.65×10-8) and 2p12 locus with valine (P-value = 3.49×10-8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.https://doi.org/10.1371/journal.pgen.1004835 |
| spellingShingle | Ayşe Demirkan Peter Henneman Aswin Verhoeven Harish Dharuri Najaf Amin Jan Bert van Klinken Lennart C Karssen Boukje de Vries Axel Meissner Sibel Göraler Arn M J M van den Maagdenberg André M Deelder Peter A C 't Hoen Cornelia M van Duijn Ko Willems van Dijk Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses. PLoS Genetics |
| title | Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses. |
| title_full | Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses. |
| title_fullStr | Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses. |
| title_full_unstemmed | Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses. |
| title_short | Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses. |
| title_sort | insight in genome wide association of metabolite quantitative traits by exome sequence analyses |
| url | https://doi.org/10.1371/journal.pgen.1004835 |
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