Dataset Information

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

ABSTRACT:

We investigated the cumulative contribution of rare, exonic genetic variants on the concentration of 1,487 metabolites and 53,714 metabolite ratios in urine by performing gene-based tests based on 226,233 variants from up to 4,864 participants of the German Chronic Kidney Disease (GCKD) study. There were 128 significant associations (53 metabolite-gene and 75 metabolite ratio-gene pairs) involving 30 unique genes, 16 of which are known to underlie recessively inherited inborn errors of metabolism (IEMs). Across the 30 genes, 47% of individuals carried at least one rare missense, stop or splice variant. The 30 genes were strongly enriched for shared high expression in liver and kidney (OR=65, p-FDR=3e-7), with hepatocytes and proximal tubule cells as driving cell types. Use of whole-exome sequencing data in the UK Biobank allowed for linking genes to diseases that could plausibly be explained by the identified metabolites. In silico constraint-based modeling of knockouts of the implicated genes in a virtual whole-body, organ-resolved metabolic human correctly predicted the observed direction of metabolite changes in urine and blood, highlighting the potential of linking population genetics to modeling to validate associations and to predict metabolic consequences of yet unknown IEMs. Our study extends the map of genes influencing urine metabolite concentrations, reveals metabolic processes and connected health outcomes, and implicates novel candidate variants and genes for IEMs.

Further links;

German Chronic Kidney Disease (GCKD)

INSTRUMENT(S): Q Exactive

SUBMITTER: Anna Kottgen

PROVIDER: MTBLS284 | MetaboLights | 2021-03-09

REPOSITORIES: MetaboLights

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Dataset's files

Source:

			Action	DRS
	MTBLS284	Other
	FILES	Other
	a_MTBLS284__Method1_POS_1_metabolite_profiling_mass_spectrometry.txt	Txt
	a_MTBLS284__Method2_POS_2_metabolite_profiling_mass_spectrometry.txt	Txt
	a_MTBLS284__Method3_NEG_1_metabolite_profiling_mass_spectrometry.txt	Txt

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Publications

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

Cheng Yurong Y Schlosser Pascal P Hertel Johannes J Sekula Peggy P Oefner Peter J PJ Spiekerkoetter Ute U Mielke Johanna J Freitag Daniel F DF Schmidts Miriam M Kronenberg Florian F Eckardt Kai-Uwe KU Thiele Ines I Li Yong Y Köttgen Anna A

Nature communications 20210211 1

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 i ...[more]

PMID: 33574263

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