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Hdr Uk Multi-omics Consortium

HDR UK Multi-omics Consortium

Description

Genetics has transformed our understanding of how variation in DNA can influence risk of developing conditions, such as cancer and heart disease. Studies that can combine this genetic information with other blood-based factors – including proteins, metabolites and lipids – and health records, have the potential to provide more direct insight into disease aetiology and prediction. A key challenge so far, however, has been accessing this information at sufficient scale.

The development of a National Multi-omics Consortium aims to address this challenge by bringing together information on participants from multiple studies to enhance scientific power, breadth, and robustness. The Consortium is one of the major initiatives within HDRUK’s Understanding the Causes of Disease programme, led by HDR UK Researcher Dr Adam Butterworth. It will bring together existing and unique data assets, maximising their value within an open and collaborative national team.

From it's conception, the Consortium was designed to include nine longitudinal UK population cohorts within the HDR UK network, comprising over 750,000 participants:

  • AIRWAVE Health Monitoring
  • COMPARE Study
  • EPIC-Norfolk
  • The Fenland Study
  • Generation Scotland
  • GoDARTS
  • INTERVAL Study
  • UCLEB Consortium
  • UK Biobank

Additional cohorts have since joined, including:

  • ALSPAC
  • Born in Bradford
  • EXCEED
  • Viking Genes (including both Viking & Orcades studies)

More info can be found here. This collection will feature datasets, projects and outputs from the HDR UK Multi-omics Consortium.

Datasets & BioSamples (7)

Avon Longitudinal Study of Parents and Children
Dataset population size: Unknown
Health and disease
COMPARE
Dataset population size: Unknown
Health and disease
INTERVAL
Dataset population size: Unknown
Health and disease
Extended Cohort for E-health, Environment and DNA (EXCEED)
Dataset population size: Unknown
Health and disease
Generation Scotland: Scottish Family Health Study
Dataset population size: 24,000
Health and disease
VIKING GENES
Dataset population size: 10,000
Health and disease

Publications (4)

A cross-platform approach identifies genetic regulators of human metabolism and health.
Lotta LA, Pietzner M, Stewart ID, Wittemans LBL, Li C, Bonelli R, Raffler J, Biggs EK, Oliver-Williams C, Auyeung VPW, Luan J, Wheeler E, Paige E, Surendran P, Michelotti GA, Scott RA, Burgess S, Zuber V, Sanderson E, Koulman A, Imamura F, Forouhi NG, Khaw KT, MacTel Consortium, Griffin JL, Wood AM, Kastenmüller G, Danesh J, Butterworth AS, Gribble FM, Reimann F, Bahlo M, Fauman E, Wareham NJ, Langenberg C.
2021
Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19.
Gaziano L, Giambartolomei C, Pereira AC, Gaulton A, Posner DC, Swanson SA, Ho YL, Iyengar SK, Kosik NM, Vujkovic M, Gagnon DR, Bento AP, Barrio-Hernandez I, Rönnblom L, Hagberg N, Lundtoft C, Langenberg C, Pietzner M, Valentine D, Gustincich S, Tartaglia GG, Allara E, Surendran P, Burgess S, Zhao JH, Peters JE, Prins BP, Angelantonio ED, Devineni P, Shi Y, Lynch KE, DuVall SL, Garcon H, Thomann LO, Zhou JJ, Gorman BR, Huffman JE, O'Donnell CJ, Tsao PS, Beckham JC, Pyarajan S, Muralidhar S, Huang GD, Ramoni R, Beltrao P, Danesh J, Hung AM, Chang KM, Sun YV, Joseph J, Leach AR, Edwards TL, Cho K, Gaziano JM, Butterworth AS, Casas JP, VA Million Veteran Program COVID-19 Science Initiative.
2021
Plasma metabolites to profile pathways in noncommunicable disease multimorbidity.
Pietzner M, Stewart ID, Raffler J, Khaw KT, Michelotti GA, Kastenmüller G, Wareham NJ, Langenberg C.
2021
Genetic architecture of host proteins involved in SARS-CoV-2 infection.
Pietzner M, Wheeler E, Carrasco-Zanini J, Raffler J, Kerrison ND, Oerton E, Auyeung VPW, Luan J, Finan C, Casas JP, Ostroff R, Williams SA, Kastenmüller G, Ralser M, Gamazon ER, Wareham NJ, Hingorani AD, Langenberg C.
2020