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Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Turcot, V; Lu, Y; Highland, HM; Schurmann, C; Justice, AE; Fine, RS; Bradfield, JP; ... Loos, RJF; + view all (2018) Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nature Genetics , 50 pp. 26-41. 10.1038/s41588-017-0011-x. Green open access

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Abstract

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

Type: Article
Title: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41588-017-0011-x
Publisher version: https://doi.org/10.1038/s41588-017-0011-x
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
URI: https://discovery.ucl.ac.uk/id/eprint/10069029
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