Dataset Information

Rare and common genetic determinants of metabolic individuality and their effects on human health (EPIC-Norfolk study assays)

ABSTRACT:

Garrod’s concept of “chemical individuality” has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P<1.25x10^-11) within 330 genomic regions, with rare variants (MAF≤1%) explaining 9.4% of associations. Jointly modelling metabolites in each region, we identified 423 regional, co-regulated, variant-metabolite clusters called GIMs (Genetically Influenced Metabotypes). We assigned causal genes for 62.4% of GIMs, providing new insights into fundamental metabolite physiology and their clinical relevance, including metabolite guided discovery of potential adverse drug effects (DPYD, SRD5A2). We show strong enrichment of Inborn Errors of Metabolism (IEM)-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of IEMs. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential aetiological relationships.

EPIC-Norfolk study assays are reported in the current study MTBLS833

INTERVAL study assays are reported in MTBLS834

INSTRUMENT(S): Q Exactive

SUBMITTER: Adam Butterworth Claudia Langenberg

PROVIDER: MTBLS833 | MetaboLights | 2022-09-09

REPOSITORIES: MetaboLights

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Dataset's files

Source:

			Action	DRS
	MTBLS833	Other
	FILES	Other
	a_MTBLS833_Method1_POS_1_metabolite_profiling_mass_spectrometry.txt	Txt
	a_MTBLS833_Method2_POS_2_metabolite_profiling_mass_spectrometry.txt	Txt
	a_MTBLS833_Method3_NEG_1_metabolite_profiling_mass_spectrometry.txt	Txt

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Publications

Rare and common genetic determinants of metabolic individuality and their effects on human health.

Surendran Praveen P Stewart Isobel D ID Au Yeung Victoria P W VPW Pietzner Maik M Raffler Johannes J Wörheide Maria A MA Li Chen C Smith Rebecca F RF Wittemans Laura B L LBL Bomba Lorenzo L Menni Cristina C Zierer Jonas J Rossi Niccolò N Sheridan Patricia A PA Watkins Nicholas A NA Mangino Massimo M Hysi Pirro G PG Di Angelantonio Emanuele E Falchi Mario M Spector Tim D TD Soranzo Nicole N Michelotti Gregory A GA Arlt Wiebke W Lotta Luca A LA Denaxas Spiros S Hemingway Harry H Gamazon Eric R ER Howson Joanna M M JMM Wood Angela M AM Danesh John J Wareham Nicholas J NJ Kastenmüller Gabi G Fauman Eric B EB Suhre Karsten K Butterworth Adam S AS Langenberg Claudia C

Nature medicine 20221110 11

Garrod's concept of 'chemical individuality' has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P < 1.25 × 10-11) within 330 genomic regions, with rare variants (minor allele freq ...[more]

PMID: 36357675

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