| Title: |
Share Rare and common genetic determinants of metabolic individuality and their effects on human health |
| Authors: |
Surendran P; Stewart ID; Au Yeung VPW; Pietzner M; Raffler J; Wörheide MA; Li C; Smith RF; Wittemans LBL; Bomba L; Menni C; Zierer J; Rossi N; Sheridan PA; Watkins NA; Mangino M; Hysi PG; Di Angelantonio E; Falchi M; Spector TD; Soranzo N; Michelotti GA; Arlt W; Lotta LA; Denaxas S; Hemingway H; Gamazon ER; Howson JMM; Wood AM; Danesh J; Wareham NJ; Kastenmüller G; Fauman EB; Suhre K; Butterworth AS; Langenberg C |
| Contributors: |
P. Surendran; I. Stewart; V. Au Yeung; M. Pietzner; J. Raffler; M. Wörheide; C. Li; R. Smith; L. Witteman; L. Bomba; C. Menni; J. Zierer; N. Rossi; P. Sheridan; N. Watkin; M. Mangino; P. Hysi; E. Di Angelantonio; M. Falchi; T. Spector; N. Soranzo; G. Michelotti; W. Arlt; L. Lotta; S. Denaxa; H. Hemingway; E. Gamazon; J. Howson; A. Wood; J. Danesh; N. Wareham; G. Kastenmüller; E. Fauman; K. Suhre; A. Butterworth; C. Langenberg |
| Publication Year: |
2022 |
| Collection: |
The University of Milan: Archivio Istituzionale della Ricerca (AIR) |
| Subject Terms: |
Settore MED/01 - Statistica Medica |
| Description: |
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 frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant–metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/pmid/36357675; info:eu-repo/semantics/altIdentifier/wos/WOS:000881574700007; volume:28; issue:11; firstpage:2321; lastpage:2332; numberofpages:12; journal:NATURE MEDICINE; https://hdl.handle.net/2434/1096348 |
| DOI: |
10.1038/s41591-022-02046-0 |
| Availability: |
https://hdl.handle.net/2434/1096348; https://doi.org/10.1038/s41591-022-02046-0 |
| Rights: |
info:eu-repo/semantics/openAccess |
| Accession Number: |
edsbas.4B8095E5 |
| Database: |
BASE |