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. 2019 Jan 29;10(1):343.
doi: 10.1038/s41467-018-08259-7.

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

Samuel E Jones  1 , Jacqueline M Lane  2   3   4 , Andrew R Wood  1 , Vincent T van Hees  5 , Jessica Tyrrell  1 , Robin N Beaumont  1 , Aaron R Jeffries  1 , Hassan S Dashti  2   4 , Melvyn Hillsdon  6 , Katherine S Ruth  1 , Marcus A Tuke  1 , Hanieh Yaghootkar  1 , Seth A Sharp  1 , Yingjie Jie  1 , William D Thompson  1 , Jamie W Harrison  1 , Amy Dawes  1 , Enda M Byrne  7 , Henning Tiemeier  8   9 , Karla V Allebrandt  10 , Jack Bowden  11   12 , David W Ray  13   14 , Rachel M Freathy  1 , Anna Murray  1 , Diego R Mazzotti  15 , Philip R Gehrman  16 , Debbie A Lawlor  11   12 , Timothy M Frayling  1 , Martin K Rutter  13   14   17 , David A Hinds  18 , Richa Saxena  2   3   19 , Michael N Weedon  20
Affiliations

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

Samuel E Jones et al. Nat Commun. .

Abstract

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.

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Conflict of interest statement

D.A.L. receives support from Roche Diagnostics and Medtronic for research that is unrelated to this study. M.K.R. reports receiving honoraria and consulting fees from Novo Nordisk, Ascensia, Cell Catapult and Roche Diabetes Care. K.V.A. received support from SANOFI-Aventis for research that is unrelated to this study. D.A.H. and 2.R.T. are employees of, and hold stock or stock options in, 23andMe Inc. The remaining authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Manhattan plot of the chronotype meta-analysis GWAS. The solid line indicates the typical genome-wide significance threshold of P = 5  × 10−8 and the dashed line marks the threshold of P = 6 × 10−9 identified through permutation testing. Lead variants are annotated with a diamond
Fig. 2
Fig. 2
Reactome gene sets overlapping Chronotype genes. Chronotype genes were identified using positional and eQTL mapping in FUMA’s GENE2FUNC process. Note that these results may differ to those produced by MAGMA
Fig. 3
Fig. 3
WikiPathways gene sets overlapping Chronotype genes. Chronotype genes were identified using positional and eQTL mapping in FUMA’s GENE2FUNC process. Note that these results may differ to those produced by MAGMA
Fig. 4
Fig. 4
MAGMA tissue expression analysis results. Per-tissue enrichment of expression of chronotype genes based on GTEx RNA-seq data for a 30 general and b 53 specific tissue types
Fig. 5
Fig. 5
MR scatter plot of schizophrenia risk vs. chronotype exposure. Plot shows chronotype meta-analysis variants and their effects (log odds ratios) on schizophrenia risk in the PGC GWAS (outcome) versus odds of being a morning person (exposure). Lines identify the slopes of the five methods tested. Log odds (and SEs) for morningness were taken from the secondary effect-size meta-analysis. Error bars represent standard errors of effect sizes
Fig. 6
Fig. 6
MR scatter plot of subjective well-being outcome vs. chronotype exposure. Plot showing chronotype meta-analysis variants and their effects (log odds ratios) on subjective well-being in the SSGAC GWAS (outcome) versus odds of being a morning person (exposure). Lines identify the slopes of the five methods tested. Log odds (and SEs) for morningness were taken from the secondary effect-size meta-analysis. Error bars represent standard errors of effect sizes
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