Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function
Abstract Dissecting the genetic mechanisms underlying urinary metabolite concentrations can provide molecular insights into kidney function and open possibilities for causal assessment of urinary metabolites with risk factors and disease outcomes. Proton nuclear magnetic resonance metabolomics provi...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-55182-1 |
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| author | Erkka Valo Anne Richmond Stefan Mutter Emma H. Dahlström Archie Campbell David J. Porteous James F. Wilson FinnDiane Study Group Per-Henrik Groop Caroline Hayward Niina Sandholm |
| author_facet | Erkka Valo Anne Richmond Stefan Mutter Emma H. Dahlström Archie Campbell David J. Porteous James F. Wilson FinnDiane Study Group Per-Henrik Groop Caroline Hayward Niina Sandholm |
| author_sort | Erkka Valo |
| collection | DOAJ |
| description | Abstract Dissecting the genetic mechanisms underlying urinary metabolite concentrations can provide molecular insights into kidney function and open possibilities for causal assessment of urinary metabolites with risk factors and disease outcomes. Proton nuclear magnetic resonance metabolomics provides a high-throughput means for urinary metabolite profiling, as widely applied for blood biomarker studies. Here we report a genome-wide association study meta-analysed for 3 European cohorts comprising 8,011 individuals, covering both people with type 1 diabetes and general population settings. We identify 54 associations (p < 9.3 × 10−10) for 19 of 54 studied metabolite concentrations. Out of these, 33 were not reported previously for relevant urinary or blood metabolite traits. Subsequent two-sample Mendelian randomization analysis suggests that estimated glomerular filtration rate causally affects 13 urinary metabolite concentrations whereas urinary ethanolamine, an initial precursor for phosphatidylcholine and phosphatidylethanolamine, was associated with higher eGFR lending support for a potential protective role. Our study provides a catalogue of genetic associations for 53 metabolites, enabling further investigation on how urinary metabolites are linked to human health. |
| format | Article |
| id | doaj-art-003903be461f451a9aaf6ac597495485 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-003903be461f451a9aaf6ac5974954852025-01-05T12:37:36ZengNature PortfolioNature Communications2041-17232025-01-0116111610.1038/s41467-024-55182-1Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney functionErkka Valo0Anne Richmond1Stefan Mutter2Emma H. Dahlström3Archie Campbell4David J. Porteous5James F. Wilson6FinnDiane Study GroupPer-Henrik Groop7Caroline Hayward8Niina Sandholm9Folkhälsan Research CenterCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General HospitalFolkhälsan Research CenterFolkhälsan Research CenterCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General HospitalCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General HospitalCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General HospitalFolkhälsan Research CenterCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General HospitalFolkhälsan Research CenterAbstract Dissecting the genetic mechanisms underlying urinary metabolite concentrations can provide molecular insights into kidney function and open possibilities for causal assessment of urinary metabolites with risk factors and disease outcomes. Proton nuclear magnetic resonance metabolomics provides a high-throughput means for urinary metabolite profiling, as widely applied for blood biomarker studies. Here we report a genome-wide association study meta-analysed for 3 European cohorts comprising 8,011 individuals, covering both people with type 1 diabetes and general population settings. We identify 54 associations (p < 9.3 × 10−10) for 19 of 54 studied metabolite concentrations. Out of these, 33 were not reported previously for relevant urinary or blood metabolite traits. Subsequent two-sample Mendelian randomization analysis suggests that estimated glomerular filtration rate causally affects 13 urinary metabolite concentrations whereas urinary ethanolamine, an initial precursor for phosphatidylcholine and phosphatidylethanolamine, was associated with higher eGFR lending support for a potential protective role. Our study provides a catalogue of genetic associations for 53 metabolites, enabling further investigation on how urinary metabolites are linked to human health.https://doi.org/10.1038/s41467-024-55182-1 |
| spellingShingle | Erkka Valo Anne Richmond Stefan Mutter Emma H. Dahlström Archie Campbell David J. Porteous James F. Wilson FinnDiane Study Group Per-Henrik Groop Caroline Hayward Niina Sandholm Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function Nature Communications |
| title | Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function |
| title_full | Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function |
| title_fullStr | Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function |
| title_full_unstemmed | Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function |
| title_short | Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function |
| title_sort | genome wide characterization of 54 urinary metabolites reveals molecular impact of kidney function |
| url | https://doi.org/10.1038/s41467-024-55182-1 |
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