The HUNT study: A population-based cohort for genetic research

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  • Ben M. Brumpton
  • Sarah Graham
  • Ida Surakka
  • Anne Heidi Skogholt
  • Mari Løset
  • Lars G. Fritsche
  • Brooke Wolford
  • Wei Zhou
  • Jonas Bille Nielsen
  • Oddgeir L. Holmen
  • Maiken E. Gabrielsen
  • Laurent Thomas
  • Laxmi Bhatta
  • Humaira Rasheed
  • He Zhang
  • Hyun Min Kang
  • Whitney Hornsby
  • Marta Riise Moksnes
  • Eivind Coward
  • Mads Melbye
  • And 10 others
  • Guro F. Giskeødegård
  • Jørn Fenstad
  • Steinar Krokstad
  • Marit Næss
  • Arnulf Langhammer
  • Michael Boehnke
  • Gonçalo R. Abecasis
  • Bjørn Olav Åsvold
  • Kristian Hveem
  • Cristen J. Willer

The Trøndelag Health Study (HUNT) is a population-based cohort of ∼229,000 individuals recruited in four waves beginning in 1984 in Trøndelag County, Norway. Approximately 88,000 of these individuals have available genetic data from array genotyping. HUNT participants were recruited during four community-based recruitment waves and provided information on health-related behaviors, self-reported diagnoses, family history of disease, and underwent physical examinations. Linkage via the Norwegian personal identification number integrates digitized health care information from doctor visits and national health registries including death, cancer and prescription registries. Genome-wide association studies of HUNT participants have provided insights into the mechanism of cardiovascular, metabolic, osteoporotic, and liver-related diseases, among others. Unique features of this cohort that facilitate research include nearly 40 years of longitudinal follow-up in a motivated and well-educated population, family data, comprehensive phenotyping, and broad availability of DNA, RNA, urine, fecal, plasma, and serum samples.

Original languageEnglish
Article number100193
JournalCell Genomics
Volume2
Issue number10
ISSN2666-979x
DOIs
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 The Author(s)

    Research areas

  • big data, biobank, cardiovascular health, complex disease, electronic health records, genetic epidemiology, genetics, longitudinal, omics, public health

ID: 334988705