Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism
Open accessAbstract
Metabolite levels in urine may provide insights into genetic mechanisms shaping their related pathways. We therefore investigate the cumulative contribution of rare, exonic genetic variants on urine levels of 1487 metabolites and 53,714 metabolite ratios among 4864 GCKD study participants. Here we report the detection of 128 significant associations involving 30 unique genes, 16 of which are known to underlie inborn errors of metabolism. The 30 genes are strongly enriched for shared expression in liver and kidney (odds ratio = 65, p-FDR = 3e−7), with hepatocytes and proximal tubule cells as driving cell types. Use of UK Biobank whole-exome sequencing data links genes to diseases connected to the identified metabolites. In silico constraint-based modeling of gene knockouts in a virtual whole-body, organ-resolved metabolic human correctly predicts the observed direction of metabolite changes, highlighting the potential of linking population genetics to modeling. Our study implicates candidate variants and genes for inborn errors of metabolism.
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Of the 10 exome-wide significant genes identified by SCHEMA, two were prioritised candidates from fine-mapping: GRIN2A and SP4.
“Of the 10 exome-wide significant genes identified by SCHEMA36, two were prioritised candidates from fine-mapping; GRIN2A encoding a glutamatergic NMDA receptor subunit, and SP4, a transcription factor highly expressed in brain and which is regulated by NMDA transmission, and also regulates NMDA receptor abundance37.”
From Mapping genomic loci implicates genes and synaptic biology in schizophrenia (2022) · cites this paper as [36]
The authors limited fine-mapping to regions that achieved genome-wide significance in the core PGC GWAS, since the method needs all markers in a region.
“As fine-mapping requires data from all markers in the region36 we only performed fine-mapping on regions that attained genome-wide significance (GWS) in the core PGC GWAS.”
From Mapping genomic loci implicates genes and synaptic biology in schizophrenia (2022) · cites this paper as [36]
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References 85 · Cited by 37
- Authors
- Cheng, Y., Schlosser, P., Hertel, J., Sekula, P., Oefner, P. J., Spiekerkoetter, U., Mielke, J., Freitag, D. F., Schmidts, M., GCKD Investigators, Oefner, P. J., Kronenberg, F., Eckardt, K.-U., Kronenberg, F., Eckardt, K.-U., Thiele, I., Li, Y., & Köttgen, A.
- Affiliations
- University of Freiburg (DE)
- Ollscoil na Gaillimhe – University of Galway (IE)
- Bayer (Germany) (DE)
- University of Regensburg (DE)
- Corresponding author
- Köttgen, Anna
- ORCID
- Venue
- Nature Communications
- Published
- 2021-02-11
- Volume
- 12
- Issue
- 1
- Pages
- 964-964
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC7878905
- OpenAlex
- W3127646790
- Cited by
- 37
- References
- 85
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 6 · 2023: 8 · 2022: 7 · 2021: 2
- FWCI
- 4.39
- Type
- journal article
- Language
- en
- Update notices
- correction (2021-10-06)
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- University of Regensburg Publication Server (University of Regensburg) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Lenus, The Irish Health Repository (Dr Steevens Hospital Library) (submittedVersion, cc-by)
- University of Regensburg Publication Server (University of Regensburg)
- Funders
- European Commission (757922, HORIZON2020)
- Deutsche Forschungsgemeinschaft (KO 3598/4-1, KO 3598/5-1, 431984000, SFB1453, KO 3598/4-2, 716344, CRC992)
- Bundesministerium für Bildung und Forschung (01ER0804, 431984000)
- Albert-Ludwigs-Universität Freiburg (431984000)
- KfH-Stiftung Präventivmedizin
- Medizinische Fakultät der Albert-Ludwigs-Universität Freiburg
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Metabolism and Genetic Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Keywords
- rare variants, urinary metabolites, metabolite ratios, inborn errors of metabolism, population variation, genetic association, hepatocytes, proximal tubular epithelial cells, constraint-based metabolic modeling, gene knockout, UK Biobank
- MeSH terms
- Exome Sequencing, Genotype, Humans, Kidney, Liver, Male, Metabolism, Inborn Errors, Genetic Variation, Rare Diseases
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