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Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms.

Nature communications | 2019

Being a morning person is a behavioural indicator of a person's underlying circadian rhythm. Using genome-wide data from 697,828 UK Biobank and 23andMe participants we increase the number of genetic loci associated with being a morning person from 24 to 351. Using data from 85,760 individuals with activity-monitor derived measures of sleep timing we find that the chronotype loci associate with sleep timing: the mean sleep timing of the 5% of individuals carrying the most morningness alleles is 25 min earlier than the 5% carrying the fewest. The loci are enriched for genes involved in circadian regulation, cAMP, glutamate and insulin signalling pathways, and those expressed in the retina, hindbrain, hypothalamus, and pituitary. Using Mendelian Randomisation, we show that being a morning person is causally associated with better mental health but does not affect BMI or risk of Type 2 diabetes. This study offers insights into circadian biology and its links to disease in humans.

Pubmed ID: 30696823 RIS Download

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Associated grants

  • Agency: Medical Research Council, United Kingdom
    Id: MC_PC_17228
  • Agency: Medical Research Council, United Kingdom
    Id: MR/M005070/1
  • Agency: NHLBI NIH HHS, United States
    Id: T32 HL007901
  • Agency: Wellcome Trust, United Kingdom
    Id: 107851/Z/15/Z
  • Agency: NIDDK NIH HHS, United States
    Id: F32 DK102323
  • Agency: Medical Research Council, United Kingdom
    Id: MC_UU_00011/2
  • Agency: Medical Research Council, United Kingdom
    Id: MR/P023576/2
  • Agency: Wellcome Trust, United Kingdom
  • Agency: Medical Research Council, United Kingdom
    Id: MR/P012167/1
  • Agency: NHLBI NIH HHS, United States
    Id: K01 HL136884
  • Agency: NIDDK NIH HHS, United States
    Id: R01 DK107859
  • Agency: NIDDK NIH HHS, United States
    Id: R01 DK102696
  • Agency: Medical Research Council, United Kingdom
    Id: MC_UU_12013/5
  • Agency: Medical Research Council, United Kingdom
    Id: MC_QA137853
  • Agency: NIDDK NIH HHS, United States
    Id: R01 DK105072

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METAL (tool)

RRID:SCR_002013

Software application designed to facilitate meta-analysis of large datasets (such as several whole genome scans) in a convenient, rapid and memory efficient manner. (entry from Genetic Analysis Software)

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