Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism

Cheng Y, Schlosser P, Hertel J, Sekula P, Oefner PJ, Spiekerkoetter U, Mielke J, Freitag DF, Schmidts M, Oefner PJ, Kronenberg F, Eckardt KU, Kronenberg F, Eckardt KU, Thiele I, Li Y, Köttgen A (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Nature Communications Nature Publishing Group: Nature Communications

Book Volume: 12

Article Number: 964

Journal Issue: 1

DOI: 10.1038/s41467-020-20877-8

Abstract

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.

Authors with CRIS profile

Kai-Uwe Eckardt Department of Medicine 4 – Nephrology and Hypertension

Involved external institutions

Albert-Ludwigs-Universität Freiburg DE Germany (DE) Charité - Universitätsmedizin Berlin DE Germany (DE) Medizinische Universität Innsbruck AT Austria (AT) Bayer AG DE Germany (DE) University of Galway (NUIG) / Ollscoil na Gaillimhe IE Ireland (IE) Universität Regensburg DE Germany (DE)

How to cite

APA:

Cheng, Y., Schlosser, P., Hertel, J., Sekula, P., Oefner, P.J., Spiekerkoetter, U.,... Köttgen, A. (2021). Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism. Nature Communications, 12(1). https://doi.org/10.1038/s41467-020-20877-8

MLA:

Cheng, Yurong, et al. "Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism." Nature Communications 12.1 (2021).

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