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      GWAS of 89,283 individuals identifies genetic variants associated with self-reporting of being a morning person

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          Abstract

          Circadian rhythms are a nearly universal feature of living organisms and affect almost every biological process. Our innate preference for mornings or evenings is determined by the phase of our circadian rhythms. We conduct a genome-wide association analysis of self-reported morningness, followed by analyses of biological pathways and related phenotypes. We identify 15 significantly associated loci, including seven near established circadian genes (rs12736689 near RGS16, P=7.0 × 10 −18; rs9479402 near VIP, P=3.9 × 10 −11; rs55694368 near PER2, P=2.6 × 10 −9; rs35833281 near HCRTR2, P=3.7 × 10 −9; rs11545787 near RASD1, P=1.4 × 10 −8; rs11121022 near PER3, P=2.0 × 10 −8; rs9565309 near FBXL3, P=3.5 × 10 −8. Circadian and phototransduction pathways are enriched in our results. Morningness is associated with insomnia and other sleep phenotypes; and is associated with body mass index and depression but we did not find evidence for a causal relationship in our Mendelian randomization analysis. Our findings reinforce current understanding of circadian biology and will guide future studies.

          Abstract

          Circadian rhythms and related behaviours vary across individuals. Here, a large genome-wide association study reveals common single nucleotide variants influencing whether an individual reports as being a ‘morning person' by identifying 15 significant loci, including 7 near known circadian genes.

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          Most cited references46

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          Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants.

          Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored. We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic. Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure. The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.
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            Suprachiasmatic nucleus: cell autonomy and network properties.

            The suprachiasmatic nucleus (SCN) is the primary circadian pacemaker in mammals. Individual SCN neurons in dispersed culture can generate independent circadian oscillations of clock gene expression and neuronal firing. However, SCN rhythmicity depends on sufficient membrane depolarization and levels of intracellular calcium and cAMP. In the intact SCN, cellular oscillations are synchronized and reinforced by rhythmic synaptic input from other cells, resulting in a reproducible topographic pattern of distinct phases and amplitudes specified by SCN circuit organization. The SCN network synchronizes its component cellular oscillators, reinforces their oscillations, responds to light input by altering their phase distribution, increases their robustness to genetic perturbations, and enhances their precision. Thus, even though individual SCN neurons can be cell-autonomous circadian oscillators, neuronal network properties are integral to normal function of the SCN.
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              The sleep disorder canine narcolepsy is caused by a mutation in the hypocretin (orexin) receptor 2 gene.

              Narcolepsy is a disabling sleep disorder affecting humans and animals. It is characterized by daytime sleepiness, cataplexy, and striking transitions from wakefulness into rapid eye movement (REM) sleep. In this study, we used positional cloning to identify an autosomal recessive mutation responsible for this sleep disorder in a well-established canine model. We have determined that canine narcolepsy is caused by disruption of the hypocretin (orexin) receptor 2 gene (Hcrtr2). This result identifies hypocretins as major sleep-modulating neurotransmitters and opens novel potential therapeutic approaches for narcoleptic patients.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                02 February 2016
                2016
                : 7
                : 10448
                Affiliations
                [1 ]23andMe, Inc. , 899 W Evelyn Avenue, Mountain View, California 94043 USA
                [2 ]Department of Biological Sciences, San Jose State University , San Jose, California 95112 USA
                Author notes
                [*]

                Present address: A9.com Inc, 130 Lytton Avenue, Palo Alto, California 94301, USA.

                Article
                ncomms10448
                10.1038/ncomms10448
                4740817
                26835600
                25dbd7e8-cd53-4166-b6c0-7eb082fd4361
                Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 08 August 2014
                : 11 December 2015
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