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Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

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  • Ioanna Tachmazidou
  • Dániel Süveges
  • Josine L Min
  • Graham R S Ritchie
  • Julia Steinberg
  • Klaudia Walter
  • Valentina Iotchkova
  • Jeremy Schwartzentruber
  • Jie Huang
  • Yasin Memari
  • Shane McCarthy
  • Andrew A Crawford
  • Cristina Bombieri
  • Massimiliano Cocca
  • Aliki-Eleni Farmaki
  • Tom R Gaunt
  • Pekka Jousilahti
  • Marjolein N Kooijman
  • Benjamin Lehne
  • Giovanni Malerba
  • Satu Männistö
  • Angela Matchan
  • Carolina Medina-Gomez
  • Sarah J Metrustry
  • Abhishek Nag
  • Ioanna Ntalla
  • Lavinia Paternoster
  • Nigel W Rayner
  • Cinzia Sala
  • William R Scott
  • Hashem A Shihab
  • Lorraine Southam
  • Beate St Pourcain
  • Michela Traglia
  • Katerina Trajanoska
  • Gialuigi Zaza
  • Weihua Zhang
  • María S Artigas
  • Narinder Bansal
  • Marianne Benn
  • Zhongsheng Chen
  • Petr Danecek
  • Wei-Yu Lin
  • Adam Locke
  • Jian'an Luan
  • Alisa K Manning
  • Antonella Mulas
  • Anne Tybjaerg-Hansen
  • Anette Varbo
  • Børge G Nordestgaard
  • SpiroMeta Consortium
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Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.

Original languageEnglish
JournalAmerican Journal of Human Genetics
Volume100
Issue number6
Pages (from-to)865-884
Number of pages20
ISSN0002-9297
DOIs
Publication statusPublished - 1 Jun 2017

    Research areas

  • Anthropometry, Body Height, Cohort Studies, DNA Methylation, Databases, Genetic, Female, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Lipodystrophy, Male, Meta-Analysis as Topic, Obesity, Physical Chromosome Mapping, Quantitative Trait Loci, Sequence Analysis, DNA, Sex Characteristics, Syndrome, United Kingdom, Journal Article

ID: 52188649