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Fei CJ, Li ZY, Ning J, Yang L, Wu BS, Kang JJ, Liu WS, He XY, You J, Chen SD, Yu H, Huang ZL, Feng JF, Yu JT, Cheng W. Exome sequencing identifies genes associated with sleep-related traits. Nat Hum Behav 2024; 8:576-589. [PMID: 38177695 DOI: 10.1038/s41562-023-01785-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 11/15/2023] [Indexed: 01/06/2024]
Abstract
Sleep is vital for human health and has a moderate heritability. Previous genome-wide association studies have limitations in capturing the role of rare genetic variants in sleep-related traits. Here we conducted a large-scale exome-wide association study of eight sleep-related traits (sleep duration, insomnia symptoms, chronotype, daytime sleepiness, daytime napping, ease of getting up in the morning, snoring and sleep apnoea) among 450,000 participants from UK Biobank. We identified 22 new genes associated with chronotype (ADGRL4, COL6A3, CLK4 and KRTAP3-3), daytime sleepiness (ST3GAL1 and ANKRD12), daytime napping (PLEKHM1, ANKRD12 and ZBTB21), snoring (WDR59) and sleep apnoea (13 genes). Notably, 20 of these genes were confirmed to be significantly associated with sleep disorders in the FinnGen cohort. Enrichment analysis revealed that these discovered genes were enriched in circadian rhythm and central nervous system neurons. Phenotypic association analysis showed that ANKRD12 was associated with cognition and inflammatory traits. Our results demonstrate the value of large-scale whole-exome analysis in understanding the genetic architecture of sleep-related traits and potential biological mechanisms.
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Affiliation(s)
- Chen-Jie Fei
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ze-Yu Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Jing Ning
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ju-Jiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiao-Yu He
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jia You
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Huan Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhi-Li Huang
- Department of Pharmacology, School of Basic Medical Sciences, State Key Laboratory of Medical Neurobiology, Institutes of Brain Science and Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
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Zhang W, Yang C, Zou L, Zang Y, Hu J, Hu Y, Xu C, Liu R, Wang H, Xiong Z. Combining MTI-31 with RAD001 inhibits tumor growth and invasion of kidney cancer by activating autophagy. J Appl Genet 2024; 65:103-112. [PMID: 37932653 DOI: 10.1007/s13353-023-00796-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 10/06/2023] [Accepted: 10/09/2023] [Indexed: 11/08/2023]
Abstract
At most of the times, patients who are diagnosed with kidney cancer should be provided with systemic treatment as drug resistance is a challenging issue in the treatment of this disease. The progression of the cancer can be inhibited with the help of mTOR inhibitors namely RAD001 (everolimus) and MTI-31. In literature, it has been revealed that these mTOR inhibitors have the potential to stimulate autophagy. This degradation pathway boosts the survival rate of the cancerous cells that are subjected to anti-cancer therapy. In this study, CCK8, colony formation assays, and ethynyl deoxyuridine (EdU) analysis were conducted to detect cell proliferation. Furthermore, Transwell assays were also conducted for cell migration analysis. In addition to these, the researchers also performed the flow cytometry process to identify the cells that are undergoing apoptosis. In vivo, experiments were conducted to measure the growth of tumors and metastasis. In this study, the treatment provided through a combination of MTI-31 and RAD001 significantly inhibited the kidney cancer cells' proliferation and tumor growth. Furthermore, there was a notable reduction in the migration and invasion of kidney cancer cells upon the neighboring cells. The outcomes from the mechanistic studies infer that the combination of MTI-31 and RAD001 increases the LC3 levels, which in turn translates into the activation of autophagy. To conclude, the combination of MTI-31 and RAD001 improves the anti-cancerous impact produced by RAD001 in vivo through the promotion of autophagy.
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Affiliation(s)
- Wenye Zhang
- Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, 200040, China
- Institute of Urology, Fudan University, Shanghai, 200040, China
| | - Chen Yang
- Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, 200040, China
- Institute of Urology, Fudan University, Shanghai, 200040, China
| | - Lujia Zou
- Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, 200040, China
- Institute of Urology, Fudan University, Shanghai, 200040, China
| | - Yiwen Zang
- Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
| | - Jimeng Hu
- Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, 200040, China
- Institute of Urology, Fudan University, Shanghai, 200040, China
| | - Yun Hu
- Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, 200040, China
- Institute of Urology, Fudan University, Shanghai, 200040, China
| | - Chenyang Xu
- Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, 200040, China
- Institute of Urology, Fudan University, Shanghai, 200040, China
| | - Rongzong Liu
- Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, 200040, China
- Institute of Urology, Fudan University, Shanghai, 200040, China
| | - Hao Wang
- Teaching Center of Experimental Medicine, Shanghai Medical College, Fudan University, 138 Yixueyuan Rd, Shanghai, 200032, China.
| | - Zuquan Xiong
- Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China.
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, 200040, China.
- Institute of Urology, Fudan University, Shanghai, 200040, China.
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3
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Tao Y, Qin Y, Chen S, Xu T, Lin J, Su D, Yu W, Chen X. Emerging trends and hot spots of sleep and genetic research: a bibliometric analysis of publications from 2002 to 2022 in the field. Front Neurol 2023; 14:1264177. [PMID: 38020599 PMCID: PMC10663257 DOI: 10.3389/fneur.2023.1264177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 10/04/2023] [Indexed: 12/01/2023] Open
Abstract
Background Sleep is an important biological process and has been linked to many diseases; however, very little is known about which and how genes control and regulate sleep. Although technology has seen significant development, this issue has still not been adequately resolved. Therefore, we conducted a bibliometric analysis to assess the progress in research on sleep quality and associated genes over the past 2 decades. Through our statistical data and discussions, we aimed to provide researchers with better research directions and ideas, thus promoting the advancement of this field. Methods On December 29, 2022, we utilized bibliometric techniques, such as co-cited and cluster analysis and keyword co-occurrence, using tools such as CiteSpace, VOSviewer, and the Online Analysis Platform of Literature Metrology (http://bibliometric.com/), to conduct a thorough examination of the relevant publications extracted from the Web of Science Core Collection (WoSCC). Our analysis aimed to identify the emerging trends and hot spots in this field while also predicting their potential development in future. Results Cluster analysis of the co-cited literature revealed the most popular terms relating to sleep quality and associated genes in the manner of cluster labels; these included genome-wide association studies (GWAS), circadian rhythms, obstructive sleep apnea (OSA), DNA methylation, and depression. Keyword burst detection suggested that obstructive sleep apnea, circadian clock, circadian genes, and polygenic risk score were newly emergent research hot spots. Conclusion Based on this bibliometric analysis of the publications in the last 20 years, a comprehensive analysis of the literature clarified the contributions, changes in research hot spots, and evolution of research techniques regarding sleep quality and associated genes. This research can provide medical staff and researchers with revelations into future directions of the study on the pathological mechanisms of sleep-related diseases.
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Affiliation(s)
- Ying Tao
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Anesthesiology (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China
| | - Yi Qin
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Anesthesiology (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China
| | - Sifan Chen
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Anesthesiology (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China
| | - Tian Xu
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Anesthesiology (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China
| | - Junhui Lin
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Anesthesiology (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China
| | - Diansan Su
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Anesthesiology (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China
| | - Weifeng Yu
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Anesthesiology (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China
| | - Xuemei Chen
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Anesthesiology (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China
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Austin-Zimmerman I, Levey DF, Giannakopoulou O, Deak JD, Galimberti M, Adhikari K, Zhou H, Denaxas S, Irizar H, Kuchenbaecker K, McQuillin A, Concato J, Buysse DJ, Gaziano JM, Gottlieb DJ, Polimanti R, Stein MB, Bramon E, Gelernter J. Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration. Nat Commun 2023; 14:6059. [PMID: 37770476 PMCID: PMC10539313 DOI: 10.1038/s41467-023-41249-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 08/28/2023] [Indexed: 09/30/2023] Open
Abstract
Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short ( ≤ 5 h) and long ( ≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (rg = 0.16 ± 0.04; p = 0.0002), as well as similar patterns of genetic correlation with other psychiatric and cardiometabolic phenotypes. Mendelian randomisation reveals a directional causal relationship between short sleep and depression, and a bidirectional causal relationship between long sleep and depression.
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Affiliation(s)
- Isabelle Austin-Zimmerman
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Daniel F Levey
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Olga Giannakopoulou
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- UCL Genetics Institute, Division of Biosciences, University College London, London, WC1E 6BT, UK
| | - Joseph D Deak
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Keyrun Adhikari
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Hang Zhou
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Spiros Denaxas
- Health Data Research UK, Institute of Health Informatics, University College London, London, NW1 2DA, UK
| | - Haritz Irizar
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- Department of Genetics & Genomic Sciences and Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Karoline Kuchenbaecker
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- UCL Genetics Institute, Division of Biosciences, University College London, London, WC1E 6BT, UK
| | - Andrew McQuillin
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
| | - John Concato
- School of Medicine, Yale University, New Haven, CT, 06511, USA
- Office of Medical Policy, Center for Drug Evaluation and Research, Food and Drug Administration (FDA), Silver Spring, MD, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Daniel J Gottlieb
- VA Boston Healthcare System, 1400 VFW Parkway (111PI), West Roxbury, MA, 02132, USA
- Division of Sleep and Circadian Disorders, Brigham & Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Murray B Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Departments of Psychiatry and Herbert Wertheim School of Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Elvira Bramon
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
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Scammell BH, Tchio C, Song Y, Nishiyama T, Louie TL, Dashti HS, Nakatochi M, Zee PC, Daghlas I, Momozawa Y, Cai J, Ollila HM, Redline S, Wakai K, Sofer T, Suzuki S, Lane JM, Saxena R. Multi-ancestry genome-wide analysis identifies shared genetic effects and common genetic variants for self-reported sleep duration. Hum Mol Genet 2023; 32:2797-2807. [PMID: 37384397 PMCID: PMC10656946 DOI: 10.1093/hmg/ddad101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 06/01/2023] [Accepted: 06/02/2023] [Indexed: 07/01/2023] Open
Abstract
Both short (≤6 h per night) and long sleep duration (≥9 h per night) are associated with increased risk of chronic diseases. Despite evidence linking habitual sleep duration and risk of disease, the genetic determinants of sleep duration in the general population are poorly understood, especially outside of European (EUR) populations. Here, we report that a polygenic score of 78 European ancestry sleep duration single-nucleotide polymorphisms (SNPs) is associated with sleep duration in an African (n = 7288; P = 0.003), an East Asian (n = 13 618; P = 6 × 10-4) and a South Asian (n = 7485; P = 0.025) genetic ancestry cohort, but not in a Hispanic/Latino cohort (n = 8726; P = 0.71). Furthermore, in a pan-ancestry (N = 483 235) meta-analysis of genome-wide association studies (GWAS) for habitual sleep duration, 73 loci are associated with genome-wide statistical significance. Follow-up of five loci (near HACD2, COG5, PRR12, SH3RF1 and KCNQ5) identified expression-quantitative trait loci for PRR12 and COG5 in brain tissues and pleiotropic associations with cardiovascular and neuropsychiatric traits. Overall, our results suggest that the genetic basis of sleep duration is at least partially shared across diverse ancestry groups.
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Affiliation(s)
- B H Scammell
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02215, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02141, USA
| | - C Tchio
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02215, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02141, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, GA 30310, USA
| | - Y Song
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02215, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02141, USA
| | - T Nishiyama
- Department of Public Health, Nagoya City University Graduate School of Medicine, Nagoya 467-8701, Japan
| | - T L Louie
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - H S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02215, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02141, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - M Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya 467-8701, Japan
| | - P C Zee
- Center for Circadian and Sleep Medicine, Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - I Daghlas
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02215, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02141, USA
| | - Y Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - J Cai
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - H M Ollila
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02215, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02141, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Institute for Molecular Medicine, HiLIFE, University of Helsinki, Helsinki 00014, Finland
| | - S Redline
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - K Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya 467-8701, Japan
| | - T Sofer
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - S Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medicine, Nagoya 467-8701, Japan
| | - J M Lane
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02215, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02141, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - R Saxena
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02215, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02141, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
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6
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Madrid-Valero JJ, Gregory AM. Behaviour genetics and sleep: A narrative review of the last decade of quantitative and molecular genetic research in humans. Sleep Med Rev 2023; 69:101769. [PMID: 36933344 DOI: 10.1016/j.smrv.2023.101769] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/05/2023]
Abstract
During the last decade quantitative and molecular genetic research on sleep has increased considerably. New behavioural genetics techniques have marked a new era for sleep research. This paper provides a summary of the most important findings from the last ten years, on the genetic and environmental influences on sleep and sleep disorders and their associations with health-related variables (including anxiety and depression) in humans. In this review we present a brief summary of the main methods in behaviour genetic research (such as twin and genome-wide association studies). We then discuss key research findings on: genetic and environmental influences on normal sleep and sleep disorders, as well as on the association between sleep and health variables (highlighting a substantial role for genes in individual differences in sleep and their associations with other variables). We end by discussing future lines of enquiry and drawing conclusions, including those focused on problems and misconceptions associated with research of this type. In this last decade our knowledge about genetic and environmental influences on sleep and its disorders has expanded. Both, twin and genome-wide association studies show that sleep and sleep disorders are substantially influenced by genetic factors and for the very first time multiple specific genetic variants have been associated with sleep traits and disorders.
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Affiliation(s)
- Juan J Madrid-Valero
- Department of Health Psychology, Faculty of Health Sciences, University of Alicante, Spain.
| | - Alice M Gregory
- Department of Psychology, Goldsmiths, University of London, London, United Kingdom
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7
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Raza Z, Hussain SF, Foster VS, Wall J, Coffey PJ, Martin JF, Gomes RSM. Exposure to war and conflict: The individual and inherited epigenetic effects on health, with a focus on post-traumatic stress disorder. FRONTIERS IN EPIDEMIOLOGY 2023; 3:1066158. [PMID: 38455905 PMCID: PMC10910933 DOI: 10.3389/fepid.2023.1066158] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 01/03/2023] [Indexed: 03/09/2024]
Abstract
War and conflict are global phenomena, identified as stress-inducing triggers for epigenetic modifications. In this state-of-the-science narrative review based on systematic principles, we summarise existing data to explore the outcomes of these exposures especially in veterans and show that they may result in an increased likelihood of developing gastrointestinal, auditory, metabolic and circadian issues, as well as post-traumatic stress disorder (PTSD). We also note that, despite a potential "healthy soldier effect", both veterans and civilians with PTSD exhibit the altered DNA methylation status in hypothalamic-pituitary-adrenal (HPA) axis regulatory genes such as NR3C1. Genes associated with sleep (PAX8; LHX1) are seen to be differentially methylated in veterans. A limited number of studies also revealed hereditary effects of war exposure across groups: decreased cortisol levels and a heightened (sex-linked) mortality risk in offspring. Future large-scale studies further identifying the heritable risks of war, as well as any potential differences between military and civilian populations, would be valuable to inform future healthcare directives.
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Affiliation(s)
- Zara Raza
- Research & Innovation, Blind Veterans UK, London, United Kingdom
- BRAVO VICTOR, Research & Innovation, London, United Kingdom
- Hull York Medical School, University of York, York, United Kingdom
| | - Syeda F Hussain
- Research & Innovation, Blind Veterans UK, London, United Kingdom
- BRAVO VICTOR, Research & Innovation, London, United Kingdom
| | - Victoria S Foster
- Research & Innovation, Blind Veterans UK, London, United Kingdom
- BRAVO VICTOR, Research & Innovation, London, United Kingdom
- St George's Hospital Medical School, London, United Kingdom
| | - Joseph Wall
- Hull York Medical School, University of York, York, United Kingdom
- Haxby Group Hull, General Practice Surgery, Hull, United Kingdom
| | - Peter J Coffey
- Development, Ageing and Disease, UCL Institute of Ophthalmology, University College London, London, United Kingdom
| | - John F Martin
- Centre for Cardiovascular Biology and Medicine, University College London, London, United Kingdom
| | - Renata S M Gomes
- Research & Innovation, Blind Veterans UK, London, United Kingdom
- BRAVO VICTOR, Research & Innovation, London, United Kingdom
- Northern Hub for Veterans and Military Families Research, Department of Nursing, Midwifery and Health, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, United Kingdom
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8
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Lee S, Bijsterbosch JD, Almagro FA, Elliott L, McCarthy P, Taschler B, Sala-Llonch R, Beckmann CF, Duff EP, Smith SM, Douaud G. Amplitudes of resting-state functional networks - investigation into their correlates and biophysical properties. Neuroimage 2023; 265:119779. [PMID: 36462729 PMCID: PMC10933815 DOI: 10.1016/j.neuroimage.2022.119779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 10/31/2022] [Accepted: 11/21/2022] [Indexed: 12/05/2022] Open
Abstract
Resting-state fMRI studies have shown that multiple functional networks, which consist of distributed brain regions that share synchronised spontaneous activity, co-exist in the brain. As these resting-state networks (RSNs) have been thought to reflect the brain's intrinsic functional organization, intersubject variability in the networks' spontaneous fluctuations may be associated with individuals' clinical, physiological, cognitive, and genetic traits. Here, we investigated resting-state fMRI data along with extensive clinical, lifestyle, and genetic data collected from 37,842 UK Biobank participants, with the object of elucidating intersubject variability in the fluctuation amplitudes of RSNs. Functional properties of the RSN amplitudes were first examined by analyzing correlations with the well-established between-network functional connectivity. It was found that a network amplitude is highly correlated with the mean strength of the functional connectivity that the network has with the other networks. Intersubject clustering analysis showed the amplitudes are most strongly correlated with age, cardiovascular factors, body composition, blood cell counts, lung function, and sex, with some differences in the correlation strengths between sensory and cognitive RSNs. Genome-wide association studies (GWASs) of RSN amplitudes identified several significant genetic variants reported in previous GWASs for their implications in sleep duration. We provide insight into key factors determining RSN amplitudes and demonstrate that intersubject variability of the amplitudes primarily originates from differences in temporal synchrony between functionally linked brain regions, rather than differences in the magnitude of raw voxelwise BOLD signal changes. This finding additionally revealed intriguing differences between sensory and cognitive RSNs with respect to sex effects on temporal synchrony and provided evidence suggesting that synchronous coactivations of functionally linked brain regions, and magnitudes of BOLD signal changes, may be related to different genetic mechanisms. These results underscore that intersubject variability of the amplitudes in health and disease need to be interpreted largely as a measure of the sum of within-network temporal synchrony and amplitudes of BOLD signals, with a dominant contribution from the former.
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Affiliation(s)
- Soojin Lee
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Pacific Parkinson's Research Institute, University of British Columbia, Canada.
| | - Janine D Bijsterbosch
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Mallinckrodt Institute of Radiology, Washington University Medical School, Washington University in St Louis, USA
| | - Fidel Alfaro Almagro
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Lloyd Elliott
- Department of Statistics and Actuarial Science, Simon Fraser University (SFU), Canada
| | - Paul McCarthy
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Bernd Taschler
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Roser Sala-Llonch
- Department of Biomedicine, Institute of Neurosciences, University of Barcelona, Spain
| | - Christian F Beckmann
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Eugene P Duff
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Department of Brain Sciences, Imperial College London, UK Dementia Research Institute, London UK
| | - Stephen M Smith
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Gwenaëlle Douaud
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
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9
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Lane JM, Qian J, Mignot E, Redline S, Scheer FAJL, Saxena R. Genetics of circadian rhythms and sleep in human health and disease. Nat Rev Genet 2023; 24:4-20. [PMID: 36028773 PMCID: PMC10947799 DOI: 10.1038/s41576-022-00519-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/30/2022] [Indexed: 12/13/2022]
Abstract
Circadian rhythms and sleep are fundamental biological processes integral to human health. Their disruption is associated with detrimental physiological consequences, including cognitive, metabolic, cardiovascular and immunological dysfunctions. Yet many of the molecular underpinnings of sleep regulation in health and disease have remained elusive. Given the moderate heritability of circadian and sleep traits, genetics offers an opportunity that complements insights from model organism studies to advance our fundamental molecular understanding of human circadian and sleep physiology and linked chronic disease biology. Here, we review recent discoveries of the genetics of circadian and sleep physiology and disorders with a focus on those that reveal causal contributions to complex diseases.
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Affiliation(s)
- Jacqueline M Lane
- Center for Genomic Medicine and Department of Anaesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital; and Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Jingyi Qian
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital; and Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Emmanuel Mignot
- Center for Narcolepsy, Stanford University, Palo Alto, California, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital; and Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Frank A J L Scheer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital; and Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.
| | - Richa Saxena
- Center for Genomic Medicine and Department of Anaesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital; and Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
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10
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Harbison ST. What have we learned about sleep from selective breeding strategies? Sleep 2022; 45:zsac147. [PMID: 36111812 PMCID: PMC9644121 DOI: 10.1093/sleep/zsac147] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 06/19/2022] [Indexed: 09/18/2023] Open
Abstract
Selective breeding is a classic technique that enables an experimenter to modify a heritable target trait as desired. Direct selective breeding for extreme sleep and circadian phenotypes in flies successfully alters these behaviors, and sleep and circadian perturbations emerge as correlated responses to selection for other traits in mice, rats, and dogs. The application of sequencing technologies to the process of selective breeding identifies the genetic network impacting the selected trait in a holistic way. Breeding techniques preserve the extreme phenotypes generated during selective breeding, generating community resources for further functional testing. Selective breeding is thus a unique strategy that can explore the phenotypic limits of sleep and circadian behavior, discover correlated responses of traits having shared genetic architecture with the target trait, identify naturally-occurring genomic variants and gene expression changes that affect trait variability, and pinpoint genes with conserved roles.
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Affiliation(s)
- Susan T Harbison
- Laboratory of Systems Genetics, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD,USA
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11
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Zhang S, Zhang W, Feng Y, Wan S, Ge J, Qu Z, Li X. Causal relationship between insomnia and tuberculosis: A bi-directional Mendelian randomization analysis. Medicine (Baltimore) 2022; 101:e30509. [PMID: 36123897 PMCID: PMC10662851 DOI: 10.1097/md.0000000000030509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 08/05/2022] [Indexed: 10/14/2022] Open
Abstract
Previous observational studies appear to have established a bi-directional association between sleep disorders and tuberculosis. However, their conclusions are prone to be biased by confounding effects and reverse causation due to the nature of observational studies. Mendelian randomization (MR) approach provides unconfounded estimates of causal effects and overcomes the limitations of observational studies. We performed a bi-directional MR analysis to clarify whether there existed a causal effect of insomnia on tuberculosis, or tuberculosis on insomnia. In forward-direction MR, we chose genome-wide significant (P < .5 × 10-8) and independent (r2 < 0.001) single-nucleotide polymorphisms (SNPs) as instrumental variants (IVs), then extracted effect estimates of these IVs in tuberculosis genome-wide association study (GWAS) dataset to explore causal effect of genetically proxied insomnia on tuberculosis using inverse variance-weighted (IVW), MR-Egger, and weighted median methods. Additionally, we examined robustness and pleiotropy of effect estimates by heterogeneity and sensitivity analysis. Similarly, we investigated causal effect of genetically proxied tuberculosis on insomnia in reverse-direction MR. We revealed no causal relationship between genetically proxied insomnia and tuberculosis using 15 SNPs in forward-direction MR (IVW OR 5.305 [0.100-281.341], P = .410) and reverse-direction MR analysis (ORs and P values were not applicable due to no eligible SNPs in GWAS), with insignificant heterogeneity (Q = 22.6, I2 < 0.001, P = .066) and pleiotropy (intercept = 0.032, SE = 0.057, P = .592) in effect estimates. Our bi-directional MR analysis affirms no causal effect of insomnia on tuberculosis, or tuberculosis on insomnia.
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Affiliation(s)
- Shaobin Zhang
- Department of Surgery, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
| | - Wei Zhang
- Department of Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
| | - Yan Feng
- Department of Tuberculosis, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
| | - Shiqian Wan
- Department of Infectious Diseases, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
| | - Jing Ge
- Department of Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
| | - Zhaohui Qu
- Department of Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
| | - Xin Li
- Department of Surgery, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
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12
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Yang Q, Magnus MC, Kilpi F, Santorelli G, Soares AG, West J, Magnus P, Wright J, Håberg SE, Sanderson E, Lawlor DA, Tilling K, Borges MC. Investigating causal relations between sleep duration and risks of adverse pregnancy and perinatal outcomes: linear and nonlinear Mendelian randomization analyses. BMC Med 2022; 20:295. [PMID: 36089592 PMCID: PMC9465870 DOI: 10.1186/s12916-022-02494-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 07/25/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Observational studies have reported maternal short/long sleep duration to be associated with adverse pregnancy and perinatal outcomes. However, it remains unclear whether there are nonlinear causal effects. Our aim was to use Mendelian randomization (MR) and multivariable regression to examine nonlinear effects of sleep duration on stillbirth (MR only), miscarriage (MR only), gestational diabetes, hypertensive disorders of pregnancy, perinatal depression, preterm birth and low/high offspring birthweight. METHODS We used data from European women in UK Biobank (N=176,897), FinnGen (N=~123,579), Avon Longitudinal Study of Parents and Children (N=6826), Born in Bradford (N=2940) and Norwegian Mother, Father and Child Cohort Study (MoBa, N=14,584). We used 78 previously identified genetic variants as instruments for sleep duration and investigated its effects using two-sample, and one-sample nonlinear (UK Biobank only), MR. We compared MR findings with multivariable regression in MoBa (N=76,669), where maternal sleep duration was measured at 30 weeks. RESULTS In UK Biobank, MR provided evidence of nonlinear effects of sleep duration on stillbirth, perinatal depression and low offspring birthweight. Shorter and longer duration increased stillbirth and low offspring birthweight; shorter duration increased perinatal depression. For example, longer sleep duration was related to lower risk of low offspring birthweight (odds ratio 0.79 per 1 h/day (95% confidence interval: 0.67, 0.93)) in the shortest duration group and higher risk (odds ratio 1.40 (95% confidence interval: 1.06, 1.84)) in the longest duration group, suggesting shorter and longer duration increased the risk. These were supported by the lack of evidence of a linear effect of sleep duration on any outcome using two-sample MR. In multivariable regression, risks of all outcomes were higher in the women reporting <5 and ≥10 h/day sleep compared with the reference category of 8-9 h/day, despite some wide confidence intervals. Nonlinear models fitted the data better than linear models for most outcomes (likelihood ratio P-value=0.02 to 3.2×10-52), except for gestational diabetes. CONCLUSIONS Our results show shorter and longer sleep duration potentially causing higher risks of stillbirth, perinatal depression and low offspring birthweight. Larger studies with more cases are needed to detect potential nonlinear effects on hypertensive disorders of pregnancy, preterm birth and high offspring birthweight.
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Affiliation(s)
- Qian Yang
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Maria C Magnus
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Fanny Kilpi
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gillian Santorelli
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Ana Gonçalves Soares
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jane West
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Siri Eldevik Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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13
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Abstract
Genetics is one of the various approaches adopted to understand and control mammalian sleep. Reverse genetics, which is usually applied to analyze sleep in gene-deficient mice, has been the mainstream field of genetic studies on sleep for the past three decades and has revealed that various molecules, including orexin, are involved in sleep regulation. Recently, forward genetic studies in humans and mice have identified gene mutations responsible for heritable sleep abnormalities, such as SIK3, NALCN, DEC2, the neuropeptide S receptor, and β1 adrenergic receptor. Furthermore, the protein kinase A-SIK3 pathway was shown to represent the intracellular neural signaling for sleep need. Large-scale genome-wide analyses of human sleep have been conducted, and many gene loci associated with individual differences in sleep have been found. The development of genome-editing technology and gene transfer by an adeno-associated virus has updated and expanded the genetic studies on mammals. These efforts are expected to elucidate the mechanisms of sleep–wake regulation and develop new therapeutic interventions for sleep disorders.
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Affiliation(s)
- Hiromasa Funato
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Tsukuba, Ibaraki 305-8575, Japan
- Department of Anatomy, Faculty of Medicine, Toho University, Ota-ku, Tokyo 951-8585, Japan
| | - Masashi Yanagisawa
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Tsukuba, Ibaraki 305-8575, Japan
- Department of Molecular Genetics, University of Texas Southwestern Medical Center, Dallas 75390, Texas, USA
- Life Science Center, Tsukuba Advanced Research Alliance, University of Tsukuba, Tsukuba, Ibaraki 305-8577, Japan
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14
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Wang S, Li Z, Wang X, Guo S, Sun Y, Li G, Zhao C, Yuan W, Li M, Li X, Ai S. Associations between sleep duration and cardiovascular diseases: A meta-review and meta-analysis of observational and Mendelian randomization studies. Front Cardiovasc Med 2022; 9:930000. [PMID: 36035915 PMCID: PMC9403140 DOI: 10.3389/fcvm.2022.930000] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 07/21/2022] [Indexed: 12/17/2022] Open
Abstract
The associations between sleep duration and cardiovascular diseases (CVDs) have been explored in many observational studies. However, the causality of sleep duration and many CVDs, such as coronary artery disease (CAD), heart failure (HF), and stroke, remains unclear. In this study, we conducted a systematic meta-review and meta-analysis of the results of observational and Mendelian randomization (MR) studies to examine how sleep duration impacts the risk of CVDs. We searched articles published in English and before 10 September 2021 in PubMed, Web of Science, and Embase. The articles were screened independently by two reviewers to minimize potential bias. We combined the meta-analyses of observational studies and 11 MR studies and summarized evidence of the effect of sleep duration on the risk of CAD, HF, stroke, and cardiovascular and all-cause mortality. Results showed that (a) evidence is accumulating that short sleep duration is a causal risk factor for CAD and HF; (b) abundant evidence from observational studies supports that long sleep duration is associated with the risk of CAD, stroke, and mortality, and long sleep duration has no causal associations with stroke and CAD in the MR studies; the causation of long sleep duration and other CVDs should be further studied; and (c) emerging evidence indicates that an increase in hours of sleep is associated with a decreased risk of CAD. Finally, we discussed the underlying pathophysiological mechanisms underlying short sleep duration and CVDs and suggested that increasing sleep duration benefits cardiovascular health.
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15
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Sonti S, Grant SFA. Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits. Sleep 2022; 45:6652497. [PMID: 35908176 PMCID: PMC9548675 DOI: 10.1093/sleep/zsac180] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 07/16/2022] [Indexed: 01/04/2023] Open
Abstract
Abstract
Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.
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Affiliation(s)
- Shilpa Sonti
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia , Philadelphia, PA , USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia , Philadelphia, PA , USA
- Department of Genetics, University of Pennsylvania , Philadelphia, PA , USA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA , USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine , Philadelphia, PA , USA
- Division of Human Genetics and Endocrinology, Children’s Hospital of Philadelphia , Philadelphia, PA , USA
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16
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Tran S, Prober DA. Validation of Candidate Sleep Disorder Risk Genes Using Zebrafish. Front Mol Neurosci 2022; 15:873520. [PMID: 35465097 PMCID: PMC9021570 DOI: 10.3389/fnmol.2022.873520] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 03/14/2022] [Indexed: 12/31/2022] Open
Abstract
Sleep disorders and chronic sleep disturbances are common and are associated with cardio-metabolic diseases and neuropsychiatric disorders. Several genetic pathways and neuronal mechanisms that regulate sleep have been described in animal models, but the genes underlying human sleep variation and sleep disorders are largely unknown. Identifying these genes is essential in order to develop effective therapies for sleep disorders and their associated comorbidities. To address this unmet health problem, genome-wide association studies (GWAS) have identified numerous genetic variants associated with human sleep traits and sleep disorders. However, in most cases, it is unclear which gene is responsible for a sleep phenotype that is associated with a genetic variant. As a result, it is necessary to experimentally validate candidate genes identified by GWAS using an animal model. Rodents are ill-suited for this endeavor due to their poor amenability to high-throughput sleep assays and the high costs associated with generating, maintaining, and testing large numbers of mutant lines. Zebrafish (Danio rerio), an alternative vertebrate model for studying sleep, allows for the rapid and cost-effective generation of mutant lines using the CRISPR/Cas9 system. Numerous zebrafish mutant lines can then be tested in parallel using high-throughput behavioral assays to identify genes whose loss affects sleep. This process identifies a gene associated with each GWAS hit that is likely responsible for the human sleep phenotype. This strategy is a powerful complement to GWAS approaches and holds great promise to identify the genetic basis for common human sleep disorders.
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17
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Abstract
BACKGROUND Shift work is widespread due to 24-h work in many occupations. Understanding differences in individual shift work tolerance (SWT) can help develop coping strategies for shift workers. AIMS This in-depth qualitative review elucidates the architecture of SWT, providing an overview of the research advances in the last decade (2011-2021). METHODS We searched Google Scholar, PubMed and Medline for different word combinations concerning SWT. Genome-wide association studies (GWAS) for the potential genetic basis of SWT were additionally searched in GWAS Central and GWAS Catalogue. RESULTS Eleven new studies were published since 2011, with the proportion of longitudinal studies on SWT having more than doubled in the past decade. They consolidate prior findings (e.g. hardiness most consistently associated with SWT) and discovered additional aspects of SWT like resistance to change and job stress. The 15 large-scale GWAS identified, most of which using UK Biobank (UKB) and 23andMe data, involved mapped genes showing overlap especially within analysis of the same phenotype (e.g. PER2/3 for morningness, PAX8 for sleep duration and LINGO1 for neuroticism). Individual GWAS for additional traits such as resilience have also been published though assessments of gene overlap are not yet possible. CONCLUSIONS Progress regarding longitudinal studies on SWT has been made though a more consistent definition of SWT remains crucial for future research. Non-genetic studies on SWT suggest several important traits and factors; many of which have now also been explored using GWAS. Such evidence could serve as basis for individualized risk prediction and disease prevention approaches for night-shift workers.
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Affiliation(s)
- J Degenfellner
- Department of Epidemiology, Centre for Public Health, Medical University of Vienna, 1090 Vienna, Austria
| | - E Schernhammer
- Department of Epidemiology, Centre for Public Health, Medical University of Vienna, 1090 Vienna, Austria.,Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.,Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
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18
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Leso V, Fontana L, Finiello F, De Cicco L, Luigia Ercolano M, Iavicoli I. Noise induced epigenetic effects: A systematic review. Noise Health 2021; 22:77-89. [PMID: 33402608 PMCID: PMC8000140 DOI: 10.4103/nah.nah_17_20] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Background: Noise-induced hearing loss (NIHL) is one of the leading causes of acquired sensorineural hearing loss. However, molecular mechanisms responsible for its pathogenesis remain to be elucidated. Epigenetic changes, i.e. DNA methylation, histone and microRNA expression modifications may function as a link between noise exposure and hearing loss. Therefore, the aim of the present review was to assess whether epigenetic alterations may serve as biomarkers of noise exposure or early effect. Materials and Methods: A systematic review of studies available in Pubmed, Scopus, and ISI Web of Science databases was performed. Results: Noise exposure was able to induce alterations in DNA methylation levels in workers and animal models, resulting in expression changes of genes related to hearing loss and also to extra-auditory effects. Differently expressed microRNAs were determined in NIHL workers compared to noise-exposed subjects with normal hearing, supporting their possible role as biomarkers of effect. Acoustic trauma affected histon acethylation and methylation levels in animals, suggesting their influence in the pathogenesis of acute noise-induced damage and their role as targets for potential therapeutic treatments. Conclusions: Although preliminary data suggest a relationship between noise and epigenetic effects, the limited number of studies, their different methodologies and the lack of adequate characterization of acoustic insults prevent definite conclusions. In this context, further research aimed to define the epigenetic impact of workplace noise exposure and the role of such alterations in predicting hearing loss may be important for the adoption of correct risk assessment and management strategies in occupational settings.
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Affiliation(s)
- Veruscka Leso
- Section of Occupational Medicine, Department of Public Health, University of Naples Federico II, Naples, Italy
| | - Luca Fontana
- Section of Occupational Medicine, Department of Public Health, University of Naples Federico II, Naples, Italy
| | - Ferdinando Finiello
- Section of Occupational Medicine, Department of Public Health, University of Naples Federico II, Naples, Italy
| | - Luigi De Cicco
- Section of Occupational Medicine, Department of Public Health, University of Naples Federico II, Naples, Italy
| | - Maria Luigia Ercolano
- Section of Occupational Medicine, Department of Public Health, University of Naples Federico II, Naples, Italy
| | - Ivo Iavicoli
- Section of Occupational Medicine, Department of Public Health, University of Naples Federico II, Naples, Italy
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19
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Webb JM, Fu YH. Recent advances in sleep genetics. Curr Opin Neurobiol 2021; 69:19-24. [PMID: 33360546 PMCID: PMC8217384 DOI: 10.1016/j.conb.2020.11.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 10/27/2020] [Accepted: 11/15/2020] [Indexed: 12/14/2022]
Abstract
Sleep regulation has a strong genetic component. In this review, we highlight the recent advances in sleep genetics from knockout, point mutation, and GWAS studies. We overview specific genetic effects on REM versus NREM sleep as well as how the implicated genes fall in broad functional categories. Furthermore, we elucidate how genes affect different aspects of sleep including sleep duration, sleep consolidation, recovery sleep, and the circadian timing of sleep, demonstrating that genetic studies can be powerful in understanding how the body regulates sleep.
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Affiliation(s)
- John M Webb
- Department of Neurology, Weill Institute for Neurosciences, Kavli Institute for Fundamental Neuroscience, University of California San Francisco, San Francisco, CA 94143, USA
| | - Ying-Hui Fu
- Department of Neurology, Weill Institute for Neurosciences, Kavli Institute for Fundamental Neuroscience, University of California San Francisco, San Francisco, CA 94143, USA.
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20
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Plante DT, Papale LA, Madrid A, Cook JD, Prairie ML, Alisch RS. PAX8/PAX8-AS1 DNA methylation levels are associated with objective sleep duration in persons with unexplained hypersomnolence using a deep phenotyping approach. Sleep 2021; 44:6305146. [PMID: 34145460 DOI: 10.1093/sleep/zsab108] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 12/09/2020] [Indexed: 11/13/2022] Open
Abstract
STUDY OBJECTIVES Patients with unexplained hypersomnolence have significant impairment related to daytime sleepiness and excessive sleep duration, the biological bases of which are poorly understood. This investigation sought to examine relationships between objectively measured hypersomnolence phenotypes and epigenetic modification of candidate hypersomnolence genes to advance this line of inquiry. METHODS Twenty-eight unmedicated clinical patients with unexplained hypersomnolence were evaluated using overnight ad libitum polysomnography, multiple sleep latency testing, infrared pupillometry, and the psychomotor vigilance task. DNA methylation levels on CpG sites annotated to 11 a priori hypersomnolence candidate genes were assessed for statistical association with hypersomnolence measures using independent regression models with adjusted local index of significance (aLIS) P-value threshold of 0.05. RESULTS Nine CpG sites exhibited significant associations between DNA methylation levels and total sleep time measured using ad libitum polysomnography (aLIS p-value < .05). All nine differentially methylated CpG sites were annotated to the paired box 8 (PAX8) gene and its related antisense gene (PAX8-AS1). Among these nine differentially methylated positions was a cluster of five CpG sites located in the body of the PAX8 gene and promoter of PAX8-AS1. CONCLUSIONS This study demonstrates that PAX8/PAX8-AS1 DNA methylation levels are associated with total sleep time in persons with unexplained hypersomnolence. Given prior investigations that have implicated single nucleotide polymorphisms in PAX8/PAX8-AS1 with habitual sleep duration, further research that clarifies the role of DNA methylation levels on these genes in the phenotypic expression of total sleep time is warranted.
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Affiliation(s)
| | | | - Andy Madrid
- Department of Neurological Surgery, Madison, WI.,Neuroscience Training Program, University of Wisconsin - Madison, Madison, WI
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21
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Dashti HS, Ordovás JM. Genetics of Sleep and Insights into Its Relationship with Obesity. Annu Rev Nutr 2021; 41:223-252. [PMID: 34102077 DOI: 10.1146/annurev-nutr-082018-124258] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Considerable recent advancements in elucidating the genetic architecture of sleep traits and sleep disorders may provide insight into the relationship between sleep and obesity. Despite the considerable involvement of the circadian clock in sleep and metabolism, few shared genes, including FTO, were implicated in genome-wide association studies (GWASs) of sleep and obesity. Polygenic scores composed of signals from GWASs of sleep traits show largely null associations with obesity, suggesting lead variants are unique to sleep. Modest genome-wide genetic correlations are observed between many sleep traits and obesity and are largest for snoring.Notably, U-shaped positive genetic correlations with body mass index (BMI) exist for both short and long sleep durations. Findings from Mendelian randomization suggest robust causal effects of insomnia on higher BMI and, conversely, of higher BMI on snoring and daytime sleepiness. Bidirectional effects between sleep duration and daytime napping with obesity may also exist. Limited gene-sleep interaction studies suggest that achieving favorable sleep, as part of a healthy lifestyle, may attenuate genetic predisposition to obesity, but whether these improvements produce clinically meaningful reductions in obesity risk remains unclear. Investigations of the genetic link between sleep and obesity for sleep disorders other than insomnia and in populations of non-European ancestry are currently limited. Expected final online publication date for the Annual Review of Nutrition, Volume 41 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Hassan S Dashti
- Center for Genomic Medicine and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA; .,Broad Institute, Cambridge, Massachusetts 02142, USA
| | - José M Ordovás
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts 02111, USA.,Precision Nutrition and Obesity Program, IMDEA Alimentación, 28049 Madrid, Spain
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22
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Khoury S, Wang QP, Parisien M, Gris P, Bortsov AV, Linnstaedt SD, McLean SA, Tungate AS, Sofer T, Lee J, Louie T, Redline S, Kaunisto MA, Kalso EA, Munter HM, Nackley AG, Slade GD, Smith SB, Zaykin DV, Fillingim RB, Ohrbach R, Greenspan JD, Maixner W, Neely GG, Diatchenko L. Multi-ethnic GWAS and meta-analysis of sleep quality identify MPP6 as a novel gene that functions in sleep center neurons. Sleep 2021; 44:zsaa211. [PMID: 33034629 PMCID: PMC7953222 DOI: 10.1093/sleep/zsaa211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 08/28/2020] [Indexed: 11/14/2022] Open
Abstract
Poor sleep quality can have harmful health consequences. Although many aspects of sleep are heritable, the understandings of genetic factors involved in its physiology remain limited. Here, we performed a genome-wide association study (GWAS) using the Pittsburgh Sleep Quality Index (PSQI) in a multi-ethnic discovery cohort (n = 2868) and found two novel genome-wide loci on chromosomes 2 and 7 associated with global sleep quality. A meta-analysis in 12 independent cohorts (100 000 individuals) replicated the association on chromosome 7 between NPY and MPP6. While NPY is an important sleep gene, we tested for an independent functional role of MPP6. Expression data showed an association of this locus with both NPY and MPP6 mRNA levels in brain tissues. Moreover, knockdown of an orthologue of MPP6 in Drosophila melanogaster sleep center neurons resulted in decreased sleep duration. With convergent evidence, we describe a new locus impacting human variability in sleep quality through known NPY and novel MPP6 sleep genes.
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Affiliation(s)
- Samar Khoury
- The Alan Edwards Centre for Research on Pain, McGill University, Montréal, QC, Canada
| | - Qiao-Ping Wang
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-Sen University, Guangzhou, China
| | - Marc Parisien
- The Alan Edwards Centre for Research on Pain, McGill University, Montréal, QC, Canada
| | - Pavel Gris
- The Alan Edwards Centre for Research on Pain, McGill University, Montréal, QC, Canada
| | - Andrey V Bortsov
- Center for Translational Pain Medicine, Department of Anesthesiology, Duke University, Durham, NC
| | - Sarah D Linnstaedt
- Institute for Trauma Recovery and Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Samuel A McLean
- Institute for Trauma Recovery and Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Andrew S Tungate
- Institute for Trauma Recovery and Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Tamar Sofer
- Department of Medicine, Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Jiwon Lee
- Department of Medicine, Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Susan Redline
- Department of Medicine, Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Mari Anneli Kaunisto
- Department of Diagnostics and Therapeutics, University of Helsinki, Helsinki, Finland
| | - Eija A Kalso
- Department of Diagnostics and Therapeutics, University of Helsinki, Helsinki, Finland
| | | | - Andrea G Nackley
- Center for Translational Pain Medicine, Department of Anesthesiology, Duke University, Durham, NC
| | - Gary D Slade
- School of dentistry, University of North Carolina Chapel Hill, Chapel Hill, NC
| | - Shad B Smith
- Center for Translational Pain Medicine, Department of Anesthesiology, Duke University, Durham, NC
| | - Dmitri V Zaykin
- Biostatistics and Computational Biology, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC
| | | | - Richard Ohrbach
- Department of Oral Diagnostic Services, University at Buffalo, Buffalo, NY
| | - Joel D Greenspan
- Department of Neural and Pain Sciences, Brotman Facial Pain Clinic, School of Dentistry and Center to Advance Chronic Pain Research, University of Maryland, Baltimore, MD
| | - William Maixner
- Center for Translational Pain Medicine, Department of Anesthesiology, Duke University, Durham, NC
| | - G Gregory Neely
- The Dr. John and Anne Chong Laboratory for Functional Genomics, Charles Perkins Centre and School of Life & Environmental Sciences, The University of Sydney, Sydney, NSW, Australia
| | - Luda Diatchenko
- The Alan Edwards Centre for Research on Pain, McGill University, Montréal, QC, Canada
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23
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Bruce HA, Kochunov P, Chiappelli J, Savransky A, Carino K, Sewell J, Marshall W, Kvarta M, McMahon FJ, Ament SA, Postolache TT, O'Connell J, Shuldiner A, Mitchell B, Hong LE. Genetic versus stress and mood determinants of sleep in the Amish. Am J Med Genet B Neuropsychiatr Genet 2021; 186:113-121. [PMID: 33650257 PMCID: PMC8994156 DOI: 10.1002/ajmg.b.32840] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 01/28/2021] [Accepted: 02/10/2021] [Indexed: 12/26/2022]
Abstract
Sleep is essential to the human brain and is regulated by genetics with many features conserved across species. Sleep is also influenced by health and environmental factors; identifying replicable genetic variants contributing to sleep may require accounting for these factors. We examined how stress and mood disorder contribute to sleep and impact its heritability. Our sample included 326 Amish/Mennonite individuals with a lifestyle with limited technological interferences with sleep. Sleep measures included Pittsburgh Sleep Quality Index (PSQI), bedtime, wake time, and time to sleep onset. Current stress level, cumulative life stressors, and mood disorder were also evaluated. We estimated the heritability of sleep features and examined the impact of current stress, lifetime stress, mood diagnosis on sleep quality. The results showed current stress, lifetime stress, and mood disorder were independently associated with PSQI score (p < .05). Heritability of PSQI was low (0-0.23) before and after accounting for stress and mood. Bedtime, wake time, and minutes to sleep time did show significant heritability at 0.44, 0.42, and 0.29. However, after adjusting for shared environment, only heritability of wake time remained significant. Sleep is affected by environmental stress and mental health factors even in a society with limited technological interference with sleep. Wake time may be a more biological marker of sleep as compared to the evening measures which are more influenced by other household members. Accounting for nongenetic and partially genetic determinants of sleep particularly stress and mood disorder is likely important for improving the precision of genetic studies of sleep.
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Affiliation(s)
- Heather A. Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Joshua Chiappelli
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Anya Savransky
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Kathleen Carino
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Jessica Sewell
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Wyatt Marshall
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Mark Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Francis J. McMahon
- Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, Maryland
| | - Seth A. Ament
- Institute of Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland,Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Teodor T. Postolache
- Mood and Anxiety Program, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland,Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC) for Suicide Prevention, Colorado, Aurora,Capitol MIRECC, Baltimore, Maryland
| | - Jeff O'Connell
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland,Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Alan Shuldiner
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Inc., Tarrytown, New York
| | - Braxton Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland,Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, Maryland
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
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24
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Elgart M, Redline S, Sofer T. Machine and Deep Learning in Molecular and Genetic Aspects of Sleep Research. Neurotherapeutics 2021; 18:228-243. [PMID: 33829409 PMCID: PMC8116376 DOI: 10.1007/s13311-021-01014-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/18/2021] [Indexed: 12/11/2022] Open
Abstract
Epidemiological sleep research strives to identify the interactions and causal mechanisms by which sleep affects human health, and to design intervention strategies for improving sleep throughout the lifespan. These goals can be advanced by further focusing on the environmental and genetic etiology of sleep disorders, and by development of risk stratification algorithms, to identify people who are at risk or are affected by, sleep disorders. These studies rely on comprehensive sleep-related data which often contains complex multi-dimensional physiological and molecular measurements across multiple timepoints. Thus, sleep research is well-suited for the application of computational approaches that can handle high-dimensional data. Here, we survey recent advances in machine and deep learning together with the availability of large human cohort studies with sleep data that can jointly drive the next breakthroughs in the sleep-research field. We describe sleep-related data types and datasets, and present some of the tasks in the field that can be targets for algorithmic approaches, as well as the challenges and opportunities in pursuing them.
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Affiliation(s)
- Michael Elgart
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA USA
- Department of Medicine, Harvard Medical School, Boston, MA USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA USA
- Department of Medicine, Harvard Medical School, Boston, MA USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA USA
- Department of Medicine, Harvard Medical School, Boston, MA USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
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25
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Sleep duration: A review of genome-wide association studies (GWAS) in adults from 2007 to 2020. Sleep Med Rev 2020; 56:101413. [PMID: 33338765 DOI: 10.1016/j.smrv.2020.101413] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 08/14/2020] [Accepted: 08/17/2020] [Indexed: 12/20/2022]
Abstract
A modest body of research exists in the area of human sleep genetics, which suggests that specific sleep phenotypes are, like many other complex traits, somewhat heritable. Until 2007 research into sleep genetics relied solely on twin studies, but in the last 13 years with the advent of huge biobanks and very large-scale genome-wide association studies, the field of molecular sleep genetics has seen important advances. To date, the majority have focused on self-reported sleep duration, but in recent years genome-wide association studies of objectively-measured sleep have emerged. These genetic studies have discovered multiple common genetic variants and as such, have provided insight into potential biological pathways, causal relationships between sleep duration and important disease outcomes using Mendelian randomisation. They have also shown that the heritability of these traits may not be as high as previously estimated. This article is the first to provide a detailed review of these recent advances in the genetic epidemiology of sleep duration. Studies were identified using both the GWAS Catalog and PubMed for completeness. Focus is on the genome-wide association studies published to date, including whether and how they have elucidated important biology and advanced knowledge in the area of sleep and health.
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26
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Souto-Maior C, Serrano Negron YL, Harbison ST. Natural selection on sleep duration in Drosophila melanogaster. Sci Rep 2020; 10:20652. [PMID: 33244154 PMCID: PMC7691507 DOI: 10.1038/s41598-020-77680-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 11/10/2020] [Indexed: 11/30/2022] Open
Abstract
Sleep is ubiquitous across animal species, but why it persists is not well understood. Here we observe natural selection act on Drosophila sleep by relaxing bi-directional artificial selection for extreme sleep duration for 62 generations. When artificial selection was suspended, sleep increased in populations previously selected for short sleep. Likewise, sleep decreased in populations previously selected for long sleep when artificial selection was relaxed. We measured the corresponding changes in the allele frequencies of genomic variants responding to artificial selection. The allele frequencies of these variants reversed course in response to relaxed selection, and for short sleepers, the changes exceeded allele frequency changes that would be expected under random genetic drift. These observations suggest that the variants are causal polymorphisms for sleep duration responding to natural selection pressure. These polymorphisms may therefore pinpoint the most important regions of the genome maintaining variation in sleep duration.
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Affiliation(s)
- Caetano Souto-Maior
- Laboratory of Systems Genetics, Systems Biology Center, National Heart Lung and Blood Institute, Bethesda, MD, USA
| | - Yazmin L Serrano Negron
- Laboratory of Systems Genetics, Systems Biology Center, National Heart Lung and Blood Institute, Bethesda, MD, USA
| | - Susan T Harbison
- Laboratory of Systems Genetics, Systems Biology Center, National Heart Lung and Blood Institute, Bethesda, MD, USA.
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27
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Wang Z, Wilson CM, Ge Y, Nemes J, LaValle C, Boutté A, Carr W, Kamimori G, Haghighi F. DNA Methylation Patterns of Chronic Explosive Breaching in U.S. Military Warfighters. Front Neurol 2020; 11:1010. [PMID: 33192958 PMCID: PMC7645105 DOI: 10.3389/fneur.2020.01010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 07/31/2020] [Indexed: 02/01/2023] Open
Abstract
Background: Injuries from exposure to explosions rose dramatically during the Iraq and Afghanistan wars, which motivated investigation of blast-related neurotrauma. We have undertaken human studies involving military "breachers" -exposed to controlled, low-level blast during a 3-days explosive breaching course. Methods: We screened epigenetic profiles in peripheral blood samples from 59 subjects (in two separate U.S. Military training sessions) using Infinium MethylationEPIC BeadChips. Participants had varying numbers of exposures to blast over their military careers (empirically defined as high ≥ 40, and conversely, low < 39 breaching exposures). Daily self-reported physiological symptoms were recorded. Tinnitus, memory problems, headaches, and sleep disturbances are most frequently reported. Results: We identified 14 significantly differentially methylated regions (DMRs) within genes associated with cumulative blast exposure in participants with high relative to low cumulative blast exposure. Notably, NTSR1 and SPON1 were significantly differentially methylated in high relative to low blast exposed groups, suggesting that sleep dysregulation may be altered in response to chronic cumulative blast exposure. In comparing lifetime blast exposure at baseline (prior to exposure in current training), and top associated symptoms, we identified significant DMRs associated with tinnitus, sleep difficulties, and headache. Notably, we identified KCNN3, SOD3, MUC4, GALR1, and WDR45B, which are implicated in auditory function, as differentially methylated associated with self-reported tinnitus. These findings suggest neurobiological mechanisms behind auditory injuries in our military warfighters and are particularly relevant given tinnitus is not only a primary disability among veterans, but has also been demonstrated in active duty medical records for populations exposed to blast in training. Additionally, we found that differentially methylated regions associated with the genes CCDC68 and COMT track with sleep difficulties, and those within FMOD and TNXB track with pain and headache. Conclusion: Sleep disturbances, as well as tinnitus and chronic pain, are widely reported in U.S. military service members and veterans. As we have previously demonstrated, DNA methylation encapsulates lifetime exposure to blast. The current data support previous findings and recapitulate transcriptional regulatory alterations in genes involved in sleep, auditory function, and pain. These data uncovered novel epigenetic and transcriptional regulatory mechanism underlying the etiological basis of these symptoms.
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Affiliation(s)
- Zhaoyu Wang
- James J. Peters VA Medical Center, Medical Epigenetics, Bronx, NY, United States
| | - Caroline M. Wilson
- James J. Peters VA Medical Center, Medical Epigenetics, Bronx, NY, United States
- Icahn School of Medicine at Mount Sinai, Nash Family Department of Neuroscience, New York, NY, United States
| | - Yongchao Ge
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Jeffrey Nemes
- Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD, United States
| | - Christina LaValle
- Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD, United States
| | - Angela Boutté
- Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD, United States
| | - Walter Carr
- Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD, United States
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, United States
| | - Gary Kamimori
- Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD, United States
| | - Fatemeh Haghighi
- James J. Peters VA Medical Center, Medical Epigenetics, Bronx, NY, United States
- Icahn School of Medicine at Mount Sinai, Nash Family Department of Neuroscience, New York, NY, United States
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28
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Thorp JG, Marees AT, Ong JS, An J, MacGregor S, Derks EM. Genetic heterogeneity in self-reported depressive symptoms identified through genetic analyses of the PHQ-9. Psychol Med 2020; 50:2385-2396. [PMID: 31530331 DOI: 10.1017/s0033291719002526] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND Depression is a clinically heterogeneous disorder. Previous large-scale genetic studies of depression have explored genetic risk factors of depression case-control status or aggregated sums of depressive symptoms, ignoring possible clinical or genetic heterogeneity. METHODS We analyse data from 148 752 subjects of white British ancestry in the UK Biobank who completed nine items of a self-rated measure of current depressive symptoms: the Patient Health Questionnaire (PHQ-9). Genome-Wide Association analyses were conducted for nine symptoms and two composite measures. LD Score Regression was used to calculate SNP-based heritability (h2SNP) and genetic correlations (rg) across symptoms and to investigate genetic correlations with 25 external phenotypes. Genomic structural equation modelling was used to test the genetic factor structure across the nine symptoms. RESULTS We identified nine genome-wide significant genomic loci (8 novel), with no overlap in loci across symptoms. h2SNP ranged from 6% (concentration problems) to 9% (appetite changes). Genetic correlations ranged from 0.54 to 0.96 (all p < 1.39 × 10-3) with 30 of 36 correlations being significantly smaller than one. A two-factor model provided the best fit to the genetic covariance matrix, with factors representing 'psychological' and 'somatic' symptoms. The genetic correlations with external phenotypes showed large variation across the nine symptoms. CONCLUSIONS Patterns of SNP associations and genetic correlations differ across the nine symptoms, suggesting that current depressive symptoms are genetically heterogeneous. Our study highlights the value of symptom-level analyses in understanding the genetic architecture of a psychiatric trait. Future studies should investigate whether genetic heterogeneity is recapitulated in clinical symptoms of major depression.
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Affiliation(s)
- Jackson G Thorp
- Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Andries T Marees
- Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jue-Sheng Ong
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jiyuan An
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Stuart MacGregor
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Eske M Derks
- Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia
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29
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Wang J, Kwok MK, Au Yeung SL, Li AM, Lam S, Leung GM, Schooling CM. The effect of sleep duration on hemoglobin and hematocrit: observational and Mendelian randomization study. Sleep 2020; 43:5698179. [PMID: 31956914 DOI: 10.1093/sleep/zsz325] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 11/16/2019] [Indexed: 11/13/2022] Open
Abstract
STUDY OBJECTIVE Observationally sleep duration is positively associated with hemoglobin (Hgb), whether this association is causal and consistent by sex remains unclear. Here, we assessed the association of sleep duration with Hgb and hematocrit (Hct) observationally in late adolescence in a population-representative Chinese birth cohort "Children of 1997" with validation using Mendelian randomization (MR) in adults. METHODS In the "Children of 1997" birth cohort (recruited = 8327, included = 3144), we used multivariable linear regression to assess the adjusted associations of sleep duration (measured as time in bed) with Hgb and Hct at 17.5 years and any sex differences. Using two-sample MR, we assessed the effect of sleep duration on Hgb and Hct, based on 61 single nucleotide polymorphisms (SNPs) applied to genome-wide association studies of Hgb and Hct in adults (n = 361 194). RESULTS Observationally, self-reported sleep duration was positively associated with Hct (0.034 standard deviations [SDs] per hour, 95% confidence interval [CI] 0.019 to 0.049), but not with Hgb. Using MR longer sleep increased Hct (0.077 SD per hour, 95% CI 0.035 to 0.119) and Hgb (0.065 SD per hour, 95% CI 0.020 to 0.109) using Mendelian randomization pleiotropy residual sum and outlier (MR PRESSO), with more pronounced associations in men. CONCLUSIONS Our novel findings indicate sleep increases both Hgb and Hct, particularly in men, perhaps contributing to its restorative qualities. Potential difference by sex and the implications of these findings warrant investigation.
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Affiliation(s)
- Jiao Wang
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Man Ki Kwok
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Shiu Lun Au Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Albert Martin Li
- Department of Pediatrics, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong SAR, China
| | - Simon Lam
- Department of Pediatrics, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong SAR, China
| | - Gabriel Matthew Leung
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Catherine Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China.,CUNY School of Public Health and Health Policy, New York, NY
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30
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Zhuang Z, Gao M, Yang R, Li N, Liu Z, Cao W, Huang T. Association of physical activity, sedentary behaviours and sleep duration with cardiovascular diseases and lipid profiles: a Mendelian randomization analysis. Lipids Health Dis 2020; 19:86. [PMID: 32384904 PMCID: PMC7206776 DOI: 10.1186/s12944-020-01257-z] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 04/07/2020] [Indexed: 12/19/2022] Open
Abstract
Background Observational studies have shown that moderate-to-vigorous physical activity (MVPA), vigorous physical activity (VPA), sedentary behaviours, and sleep duration were associated with cardiovascular diseases (CVDs) and lipid levels. However, whether such observations reflect causality remain largely unknown. We aimed to investigate the causal associations of physical activity, sedentary behaviours, and sleep duration with coronary artery disease (CAD), myocardial infarction (MI), stroke and lipid levels. Methods We conducted a Mendelian randomization (MR) study using genetic variants as instruments which are associated with physical activity, sedentary behaviours, and sleep duration to examine the causal effects on CVDs and lipid levels. This study included analyses of 4 potentially modifiable factors and 7 outcomes. Thus, the threshold of statistical significance is P = 1.8 × 10− 3 (0.05/4 × 7) after Bonferroni correction. Results In the present study, there was suggestive evidence for associations of genetically predicted VPA with CAD (odds ratio, 0.65; 95% confidence intervals, 0.47–0.90; P = 0.009) and MI (0.74; 0.59–0.93; P = 0.010). However, genetically predicted VPA, MVPA, sleep duration and sedentary behaviours did not show significant associations with stroke and any lipid levels. Conclusions Our findings from the MR approach provided suggestive evidence that vigorous exercise decreased risk of CAD and MI, but not stroke. However, there was no evidence to support causal associations of MVPA,sleep duration or sedentary behaviours with cardiovascular risk and lipid levels. Translational perspective The findings of this study did not point out specific recommendations on increasing physical activity required to deliver significant health benefits. Nevertheless, the findings allowed clinicians and public health practitioners to provide advice about increasing the total amount of excising time by demonstrating that such advice can be effective. Reliable assessment of the association of physical activity levels with different subtypes of CVDs is needed to provide the basis for a comprehensive clinical approach on CVDs prevention, which can be achieved through lifestyle interventions in addition to drug therapy.
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Affiliation(s)
- Zhenhuang Zhuang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Bejing, 100191, China
| | - Meng Gao
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Bejing, 100191, China
| | - Ruotong Yang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Bejing, 100191, China
| | - Nan Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Bejing, 100191, China.,Institute of Reproductive and Child Health, Peking University/Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China, Bejing, 100191, China
| | - Zhonghua Liu
- Department of Statistics and Actuarial Science, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Weihua Cao
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Bejing, 100191, China.
| | - Tao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Bejing, 100191, China. .,Department of Global Health, School of Public Health, Peking University, Bejing, 100191, China. .,Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Bejing, 100191, China.
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Genome-wide association analysis of insomnia using data from Partners Biobank. Sci Rep 2020; 10:6928. [PMID: 32332799 PMCID: PMC7181749 DOI: 10.1038/s41598-020-63792-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 03/25/2020] [Indexed: 12/21/2022] Open
Abstract
Insomnia is one of the most prevalent and burdensome mental disorders worldwide, affecting between 10–20% of adults and up to 48% of the geriatric population. It is further associated with substance usage and dependence, as well other psychiatric disorders. In this study, we combined electronic health record (EHR) derived phenotypes and genotype information to conduct a genome wide analysis of insomnia in a 18,055 patient cohort. Diagnostic codes were used to identify 3,135 patients with insomnia. Our genome-wide association study (GWAS) identified one novel genomic risk locus on chromosome 8 (lead SNP rs17052966, p = 4.53 × 10−9, odds ratio = 1.28, se = 0.04). The heritability analysis indicated that common SNPs accounts for 7% (se = 0.02, p = 0.015) of phenotypic variation. We further conducted a large-scale meta-analysis of our results and summary statistics of two recent insomnia GWAS and 13 significant loci were identified. The genetic correlation analysis yielded a strong positive genetic correlation between insomnia and alcohol use (rG = 0.56, se = 0.14, p < 0.001), nicotine use (rG = 0.50, se = 0.12, p < 0.001) and opioid use (rG = 0.43, se = 0.18, p = 0.02) disorders, suggesting a significant common genetic risk factors between insomnia and substance use.
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Cox SR, Ritchie SJ, Allerhand M, Hagenaars SP, Radakovic R, Breen DP, Davies G, Riha RL, Harris SE, Starr JM, Deary IJ. Sleep and cognitive aging in the eighth decade of life. Sleep 2020; 42:5298134. [PMID: 30668819 PMCID: PMC6448287 DOI: 10.1093/sleep/zsz019] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Indexed: 01/23/2023] Open
Abstract
We examined associations between self-reported sleep measures and cognitive level and change (age 70-76 years) in a longitudinal, same-year-of-birth cohort study (baseline N = 1091; longitudinal N = 664). We also leveraged GWAS summary data to ascertain whether polygenic scores (PGS) of chronotype and sleep duration related to self-reported sleep, and to cognitive level and change. Shorter sleep latency was associated with significantly higher levels of visuospatial ability, processing speed, and verbal memory (β ≥ |0.184|, SE ≤ 0.075, p ≤ 0.003). Longer daytime sleep duration was significantly associated slower processing speed (β = -0.085, SE = 0.027, p = 0.001), and with steeper 6-year decline in visuospatial reasoning (β = -0.009, SE = 0.003, p = 0.008), and processing speed (β = -0.009, SE = 0.002, p < 0.001). Only longitudinal associations between longer daytime sleeping and steeper cognitive declines survived correction for important health covariates and false discovery rate (FDR). PGS of chronotype and sleep duration were nominally associated with specific self-reported sleep characteristics for most SNP thresholds (standardized β range = |0.123 to 0.082|, p range = 0.003 to 0.046), but neither PGS predicted cognitive level or change following FDR. Daytime sleep duration is a potentially important correlate of cognitive decline in visuospatial reasoning and processing speed in older age, whereas cross-sectional associations are partially confounded by important health factors. A genetic propensity toward morningness and sleep duration were weakly, but consistently, related to self-reported sleep characteristics, and did not relate to cognitive level or change.
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Affiliation(s)
- Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Stuart J Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Mike Allerhand
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Saskia P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK.,Division of Psychiatry, University of Edinburgh, Edinburgh, UK.,Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ratko Radakovic
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Faculty of Medical and Health Sciences, University of East Anglia, Norwich, UK.,Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - David P Breen
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK.,Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Renata L Riha
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Department of Sleep Medicine, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
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Genetics of Circadian and Sleep Measures in Adults: Implications for Sleep Medicine. CURRENT SLEEP MEDICINE REPORTS 2020. [DOI: 10.1007/s40675-020-00165-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Kusic DM, Roberts WN, Jarvis JP, Zhang P, Scheinfeldt LB, Rajula KD, Brenner R, Dempsey MP, Zajic SC. rs11670527 Upstream of ZNF264 Associated with Body Mass Index in the Coriell Personalized Medicine Collaborative. Mil Med 2020; 185:649-655. [PMID: 31498392 DOI: 10.1093/milmed/usz216] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
INTRODUCTION the effects of obesity on health are a concern for the military as they affect the fitness to serve of active service members, increase costs to the Military Health System, and reduce quality of life for veterans and beneficiaries. Although obesity can be influenced by behavioral and environmental factors, it has also been shown to be associated with genetic risk factors that are not fully understood. MATERIALS AND METHODS we performed a genome-wide association study of 5,251 participants in the Coriell Personalized Medicine Collaborative, which includes 2,111 Air Force participants. We applied a generalized linear model, using principal component analysis to account for population structure, and analyzed single-variant associations with body mass index (BMI) as a continuous variable, using a Bonferroni-corrected P-value threshold to account for multiplicity. RESULTS we identified one genome-wide significant locus, rs11670527, upstream of the ZNF264 gene on chromosome 19, associated with BMI. CONCLUSIONS the finding of an association between rs11670527 and BMI adds to the growing body of literature characterizing the complex genetics of obesity. These efforts may eventually inform personalized interventions aimed at achieving and maintaining healthy weight.
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Affiliation(s)
- Dara M Kusic
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ 08103
| | - Wendy N Roberts
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ 08103
| | - Joseph P Jarvis
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ 08103
| | - Pan Zhang
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ 08103
| | | | - Kaveri D Rajula
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ 08103
| | - Ruth Brenner
- Immunization Healthcare Division, Defense Health Agency, Falls Church, VA 22042
| | - Michael P Dempsey
- Defense Threat Reduction Agency, 8725 John J Kingman Rd., Fort Belvoir, VA 22060 Presented as a poster at the 2018 Military Health System Research Symposium, August 2018, Kissimmee, FL: abstract # MHSRS-18-1288
| | - Stefan C Zajic
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ 08103
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35
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Genetics of the human circadian clock and sleep homeostat. Neuropsychopharmacology 2020; 45:45-54. [PMID: 31400754 PMCID: PMC6879540 DOI: 10.1038/s41386-019-0476-7] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Revised: 07/24/2019] [Accepted: 08/01/2019] [Indexed: 01/07/2023]
Abstract
Timing and duration of sleep are controlled by the circadian system, which keeps an ~24-h internal rhythm that entrains to environmental stimuli, and the sleep homeostat, which rises as a function of time awake. There is a normal distribution across the population in how the circadian system aligns with typical day and night resulting in varying circadian preferences called chronotypes. A portion of the variation in the population is controlled by genetics as shown by the single-gene mutations that confer extreme early or late chronotypes. Similarly, there is a normal distribution across the population in sleep duration. Genetic variations have been identified that lead to a short sleep phenotype in which individuals sleep only 4-6.5 h nightly. Negative health consequences have been identified when individuals do not sleep at their ideal circadian timing or are sleep deprived relative to intrinsic sleep need. Whether familial natural short sleepers are at risk of the health consequences associated with a short sleep duration based on population data is not known. More work needs to be done to better assess for an individual's chronotype and degree of sleep deprivation to answer these questions.
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Rhodes JA, Lane JM, Vlasac IM, Rutter MK, Czeisler CA, Saxena R. Association of DAT1 genetic variants with habitual sleep duration in the UK Biobank. Sleep 2019; 42:5123695. [PMID: 30299516 DOI: 10.1093/sleep/zsy193] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Indexed: 01/29/2023] Open
Abstract
Short sleep duration has been linked to negative health effects, but is a complex phenotype with many contributing factors, including genetic. We evaluated 27 common single nucleotide polymorphisms (SNPs) in candidate genes previously reported to be associated with other sleep variables for association with self-reported habitual sleep duration in the UK Biobank in 111 975 individuals of European ancestry. Genetic variation in DAT1 (rs464049) was significantly associated with sleep duration after correction for multiple testing (p = 4.00 × 10-5), whereas SNPs correlated to a previously studied variable number tandem repeat (VNTR) in DAT1 were not significant in this population. We also replicated a previously reported association in DRD2. Independent replication of these associations and a second signal in DRD2 (rs11214607) was observed in an additional 261 870 participants of European ancestry from the UK Biobank. Meta-analysis confirmed genome-wide significant association of DAT1 rs464049 (G, beta [standard error, SE] = -0.96 [0.18] minutes/allele, p = 5.71 × 10-10) and study-wide significant association of DRD2 (rs17601612, C, beta [SE] = -0.66 [0.18] minutes/allele, p = 1.77 × 10-5; rs11214607, C, beta [SE] = 1.08 (0.24) minutes/allele, p = 1.39 × 10-6). Overall, SNPs in two dopamine-related genes were significantly associated with sleep duration, highlighting the important link of the dopamine system with adult sleep duration in humans.
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Affiliation(s)
- Jessica A Rhodes
- Department of Organismic and Evolutionary Biology, Harvard College, Cambridge, MA.,Center for Genomic Medicine and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Jacqueline M Lane
- Center for Genomic Medicine and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA
| | - Irma M Vlasac
- Center for Genomic Medicine and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Martin K Rutter
- Manchester Diabetes Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.,Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Charles A Czeisler
- Department of Organismic and Evolutionary Biology, Harvard College, Cambridge, MA.,Center for Genomic Medicine and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA.,Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA
| | - Richa Saxena
- Center for Genomic Medicine and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA.,Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA
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Wang Z, Wilson CM, Mendelev N, Ge Y, Galfalvy H, Elder G, Ahlers S, Yarnell AM, LoPresti ML, Kamimori GH, Carr W, Haghighi F. Acute and Chronic Molecular Signatures and Associated Symptoms of Blast Exposure in Military Breachers. J Neurotrauma 2019; 37:1221-1232. [PMID: 31621494 PMCID: PMC7232647 DOI: 10.1089/neu.2019.6742] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Injuries from exposure to explosions rose dramatically during the Iraq and Afghanistan wars, which motivated investigations of blast-related neurotrauma and operational breaching. In this study, military “breachers” were exposed to controlled, low-level blast during a 10-day explosive breaching course. Using an omics approach, we assessed epigenetic, transcriptional, and inflammatory profile changes in blood from operational breaching trainees, with varying levels of lifetime blast exposure, along with daily self-reported symptoms (with tinnitus, headaches, and sleep disturbances as the most frequently reported). Although acute exposure to blast did not confer epigenetic changes, specifically in DNA methylation, differentially methylated regions (DMRs) with coordinated gene expression changes associated with lifetime cumulative blast exposures were identified. The accumulative effect of blast showed increased methylation of PAX8 antisense transcript with coordinated repression of gene expression, which has been associated with sleep disturbance. DNA methylation analyses conducted in conjunction with reported symptoms of tinnitus in the low versus high blast incidents groups identified DMRS in KCNE1 and CYP2E1 genes. KCNE1 and CYP2E1 showed the expected inverse correlation between DNA methylation and gene expression, which have been previously implicated in noise-related hearing loss. Although no significant transcriptional changes were observed in samples obtained at the onset of the training course relative to chronic cumulative blast, we identified a large number of transcriptional perturbations acutely pre- versus post-blast exposure. Acutely, 67 robustly differentially expressed genes (fold change ≥1.5), including UFC1 and YOD1 ubiquitin-related proteins, were identified. Inflammatory analyses of cytokines and chemokines revealed dysregulation of MCP-1, GCSF, HGF, MCSF, and RANTES acutely after blast exposure. These data show the importance of an omics approach, revealing that transcriptional and inflammatory biomarkers capture acute low-level blast overpressure exposure, whereas DNA methylation marks encapsulate chronic long-term symptoms.
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Affiliation(s)
- Zhaoyu Wang
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Caroline M Wilson
- Medical Epigenetics, James J. Peters VA Medical Center, Bronx, New York, USA.,Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Natalia Mendelev
- Medical Epigenetics, James J. Peters VA Medical Center, Bronx, New York, USA.,Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Yongchao Ge
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Hanga Galfalvy
- Medical Epigenetics, James J. Peters VA Medical Center, Bronx, New York, USA.,Department of Biostatistics in Psychiatry, Columbia University, New York, New York, USA
| | - Gregory Elder
- Neurology Service, James J. Peters VA Medical Center, Bronx, New York, USA.,Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Stephen Ahlers
- Naval Medical Research Center, Silver Spring, Maryland, USA
| | - Angela M Yarnell
- Walter Reed Army Institute of Research, Silver Spring, Maryland, USA
| | | | - Gary H Kamimori
- Walter Reed Army Institute of Research, Silver Spring, Maryland, USA
| | - Walter Carr
- Walter Reed Army Institute of Research, Silver Spring, Maryland, USA.,Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA
| | - Fatemeh Haghighi
- Medical Epigenetics, James J. Peters VA Medical Center, Bronx, New York, USA.,Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Bragantini D, Sivertsen B, Gehrman P, Lydersen S, Güzey IC. Genetic polymorphisms associated with sleep-related phenotypes; relationships with individual nocturnal symptoms of insomnia in the HUNT study. BMC MEDICAL GENETICS 2019; 20:179. [PMID: 31718593 PMCID: PMC6852911 DOI: 10.1186/s12881-019-0916-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 10/31/2019] [Indexed: 12/21/2022]
Abstract
Background In recent years, several GWAS (genome wide association studies) of sleep-related traits have identified a number of SNPs (single nucleotides polymorphism) but their relationships with symptoms of insomnia are not known. The aim of this study was to investigate whether SNPs, previously reported in association with sleep-related phenotypes, are associated with individual symptoms of insomnia. Methods We selected participants from the HUNT study (Norway) who reported at least one symptom of insomnia consisting of sleep onset, maintenance or early morning awakening difficulties, (cases, N = 2563) compared to participants who presented no symptoms at all (controls, N = 3665). Cases were further divided in seven subgroups according to different combinations of these three symptoms. We used multinomial logistic regressions to test the association among different patterns of symptoms and 59 SNPs identified in past GWAS studies. Results Although 16 SNPS were significantly associated (p < 0.05) with at least one symptom subgroup, none of the investigated SNPs remained significant after correction for multiple testing using the false discovery rate (FDR) method. Conclusions SNPs associated with sleep-related traits do not replicate on any pattern of insomnia symptoms after multiple tests correction. However, correction in this case may be overly conservative.
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Affiliation(s)
- Daniela Bragantini
- Department of Research and Development (AFFU), Norwegian University of Science and Technology (NTNU), PO Box 3250 Sluppen, NO-7006, Trondheim, Norway. .,Department of Mental Health, Norwegian University of Science and Technology (NTNU), PO Box 3250 Sluppen, NO-7006, Trondheim, Norway. .,St. Olav's University Hospital, Division of Mental Health Care, Østmarkveien 15, NO-7040, Trondheim, Norway.
| | - Børge Sivertsen
- Department of Mental Health, Norwegian University of Science and Technology (NTNU), PO Box 3250 Sluppen, NO-7006, Trondheim, Norway.,Department of Health Promotion, Norwegian Institute of Public Health, PO Box 973 Sentrum, 5808, Bergen, Norway.,Department of Research and Innovation, Helse-Fonna HF Haugesund Hospital, PO Box 2170, 5504, Haugesund, Norway
| | - Philip Gehrman
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, 3535 Market St., Suite 670, Philadelphia, PA, 19104, USA
| | - Stian Lydersen
- Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU), Norwegian University of Science and Technology (NTNU), P.O. Box 8905, N-7491, Trondheim, Norway
| | - Ismail Cüneyt Güzey
- Department of Research and Development (AFFU), Norwegian University of Science and Technology (NTNU), PO Box 3250 Sluppen, NO-7006, Trondheim, Norway.,Department of Mental Health, Norwegian University of Science and Technology (NTNU), PO Box 3250 Sluppen, NO-7006, Trondheim, Norway.,St. Olav's University Hospital, Division of Mental Health Care, Østmarkveien 15, NO-7040, Trondheim, Norway
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Zhang M, Ryan KA, Wickwire E, Postolache TT, Xu H, Daue M, Snitker S, Pollin TI, Shuldiner AR, Mitchell BD. Self-Reported Sleep Duration and Pattern in Old Order Amish and Non-Amish Adults. J Clin Sleep Med 2019; 15:1321-1328. [PMID: 31538603 PMCID: PMC6760415 DOI: 10.5664/jcsm.7928] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2019] [Revised: 05/14/2019] [Accepted: 05/15/2019] [Indexed: 01/10/2023]
Abstract
STUDY OBJECTIVES We hypothesized that sleep duration in the Amish would be longer than in non-Amish. METHODS Sleep duration was obtained by questionnaire administered to Amish individuals (n = 3,418) and from the 2015-2016 National Health and Nutrition Examination Survey (NHANES; n = 1,912). Self-reported sleep duration was calculated as the difference in usual times that the participants went to bed at night and woke up in the morning. RESULTS In Amish (43.7 ± 16.7 years) and NHANES (50.0 ± 20.6 years), women had a longer sleep duration than men (P < .0001 in both groups) and sleep was significantly longer in those aged 18-29 years and ≥ 70 years, compared to those aged 30-69 years. Seasonal-adjusted sleep duration was shorter in Amish than that in NHANES (7.8 minutes shorter, age- and sex-adjusted P < .0001). However, Amish were less likely to report sleeping fewer than 7 hours per night (15.4% in Amish versus 20.5% in NHANES, P < .0001). Amish went to bed 80.4 minutes earlier than NHANES and arose 87.6 minutes earlier (age-, sex-, and season-adjusted P < .0001 for both). In the Amish, sleep duration was longer in clerks than in farmers (P < .0001) and was significantly correlated among household members (.15 < r < .62, P < .001), although there was no evidence that this trait was heritable (h² approximately 0) after adjustment for household. CONCLUSIONS The lower frequency of short sleepers in the Amish may contribute to the relatively lower risks of cardiometabolic diseases observed in this population. CITATION Zhang M, Ryan KA, Wickwire E, Postolache TT, Xu H, Daue M, Snitker S, Pollin TI, Shuldiner AR, Mitchell BD. Self-reported sleep duration and pattern in old order amish and non-amish adults. J Clin Sleep Med. 2019;15(9):1321-1328.
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Affiliation(s)
- Man Zhang
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Kathleen A. Ryan
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Emerson Wickwire
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
- Sleep Disorders Center, Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Teodor T. Postolache
- Mood and Anxiety Program, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
- Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC), Aurora, Colorado
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Melanie Daue
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Soren Snitker
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Toni I. Pollin
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, Maryland
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40
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Richmond RC, Anderson EL, Dashti HS, Jones SE, Lane JM, Strand LB, Brumpton B, Rutter MK, Wood AR, Straif K, Relton CL, Munafò M, Frayling TM, Martin RM, Saxena R, Weedon MN, Lawlor DA, Smith GD. Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study. BMJ 2019; 365:l2327. [PMID: 31243001 PMCID: PMC6592406 DOI: 10.1136/bmj.l2327] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/26/2019] [Indexed: 12/16/2022]
Abstract
OBJECTIVE To examine whether sleep traits have a causal effect on risk of breast cancer. DESIGN Mendelian randomisation study. SETTING UK Biobank prospective cohort study and Breast Cancer Association Consortium (BCAC) case-control genome-wide association study. PARTICIPANTS 156 848 women in the multivariable regression and one sample mendelian randomisation (MR) analysis in UK Biobank (7784 with a breast cancer diagnosis) and 122 977 breast cancer cases and 105 974 controls from BCAC in the two sample MR analysis. EXPOSURES Self reported chronotype (morning or evening preference), insomnia symptoms, and sleep duration in multivariable regression, and genetic variants robustly associated with these sleep traits. MAIN OUTCOME MEASURE Breast cancer diagnosis. RESULTS In multivariable regression analysis using UK Biobank data on breast cancer incidence, morning preference was inversely associated with breast cancer (hazard ratio 0.95, 95% confidence interval 0.93 to 0.98 per category increase), whereas there was little evidence for an association between sleep duration and insomnia symptoms. Using 341 single nucleotide polymorphisms (SNPs) associated with chronotype, 91 SNPs associated with sleep duration, and 57 SNPs associated with insomnia symptoms, one sample MR analysis in UK Biobank provided some supportive evidence for a protective effect of morning preference on breast cancer risk (0.85, 0.70, 1.03 per category increase) but imprecise estimates for sleep duration and insomnia symptoms. Two sample MR using data from BCAC supported findings for a protective effect of morning preference (inverse variance weighted odds ratio 0.88, 95% confidence interval 0.82 to 0.93 per category increase) and adverse effect of increased sleep duration (1.19, 1.02 to 1.39 per hour increase) on breast cancer risk (both oestrogen receptor positive and oestrogen receptor negative), whereas evidence for insomnia symptoms was inconsistent. Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy. CONCLUSIONS Findings showed consistent evidence for a protective effect of morning preference and suggestive evidence for an adverse effect of increased sleep duration on breast cancer risk.
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Affiliation(s)
- Rebecca C Richmond
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Emma L Anderson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Hassan S Dashti
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Samuel E Jones
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Jacqueline M Lane
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Linn Beate Strand
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health sciences, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Ben Brumpton
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health sciences, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
- Clinic of Thoracic and Occupational Medicine, St Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Martin K Rutter
- Division of Endocrinology, Diabetes and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Manchester Diabetes Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, Manchester, UK
| | - Andrew R Wood
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Kurt Straif
- International Agency for Research on Cancer, Lyon, France
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marcus Munafò
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- School of Experimental Psychology, University of Bristol, Bristol, UK
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Richa Saxena
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Anaesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael N Weedon
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
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Wang J, Li AM, Lam HSHS, Leung GM, Schooling CM. Sleep Duration and Adiposity in Children and Adults: Observational and Mendelian Randomization Studies. Obesity (Silver Spring) 2019; 27:1013-1022. [PMID: 31067017 DOI: 10.1002/oby.22469] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 02/13/2019] [Indexed: 02/04/2023]
Abstract
OBJECTIVE This study used two complementary designs, an observational and a Mendelian randomization (MR) study, to assess whether sleep duration causes adiposity in children and adults. METHODS In Hong Kong's "Children of 1997" birth cohort, the adjusted cross-sectional associations of sleep duration with BMI z score and obesity and overweight were assessed at ~11 years of age. Generalized estimating equations were also used to examine longitudinal associations of sleep duration at ~11 years with annual BMI z score and obesity and overweight at about 11 to 16 years of age. Using MR, this study assessed the association of genetically predicted sleep duration, based on 54 single-nucleotide polymorphisms, applied to genetic studies of adiposity in children (n = 35,668), men (n = 152,893), and women (n = 171,977). RESULTS Longer sleep was cross-sectionally associated with lower BMI z score at ~11 years of age (-0.13 per category, 95% CI: -0.22 to -0.04) and at about 11 to 16 years of age longitudinally in girls (-0.39, 95% CI: -0.66 to -0.13). Using MR, sleep duration was inversely associated with BMI in children (-0.29 SD per hour, 95% CI: -0.54 to -0.04), but was not clearly associated with BMI in adults, particularly for women. CONCLUSIONS A small beneficial effect of sleep on BMI in children cannot be ruled out.
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Affiliation(s)
- Jiao Wang
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Albert M Li
- Department of Pediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Hugh S Hung San Lam
- Department of Pediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Gabriel M Leung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- CUNY School of Public Health and Health Policy, City University of New York, New York, New York, USA
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42
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Jones SE, van Hees VT, Mazzotti DR, Marques-Vidal P, Sabia S, van der Spek A, Dashti HS, Engmann J, Kocevska D, Tyrrell J, Beaumont RN, Hillsdon M, Ruth KS, Tuke MA, Yaghootkar H, Sharp SA, Ji Y, Harrison JW, Freathy RM, Murray A, Luik AI, Amin N, Lane JM, Saxena R, Rutter MK, Tiemeier H, Kutalik Z, Kumari M, Frayling TM, Weedon MN, Gehrman PR, Wood AR. Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour. Nat Commun 2019; 10:1585. [PMID: 30952852 PMCID: PMC6451011 DOI: 10.1038/s41467-019-09576-1] [Citation(s) in RCA: 154] [Impact Index Per Article: 30.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 03/14/2019] [Indexed: 01/16/2023] Open
Abstract
Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P < 5 × 10-8, of which 20 reach a stricter threshold of P < 8 × 10-10. These include 26 novel associations with measures of sleep quality and 10 with nocturnal sleep duration. The majority of identified variants associate with a single sleep trait, except for variants previously associated with restless legs syndrome. For sleep duration we identify a missense variant (p.Tyr727Cys) in PDE11A as the likely causal variant. As a group, sleep quality loci are enriched for serotonin processing genes. Although accelerometer-derived measures of sleep are imperfect and may be affected by restless legs syndrome, these findings provide new biological insights into sleep compared to previous efforts based on self-report sleep measures.
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Affiliation(s)
- Samuel E Jones
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | | | - Diego R Mazzotti
- Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, 19104, PA, USA
- Perelman School of Medicine of the University of Pennsylvania, Philadelphia, 19104, PA, USA
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, 1011, Switzerland
| | - Séverine Sabia
- Research Department of Epidemiology and Public Health, University College London, London, WC1E 6BT, UK
- INSERM, U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, Paris, 75010, France
| | - Ashley van der Spek
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, 3000 CA, The Netherlands
| | - Hassan S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Jorgen Engmann
- UCL Institute of Cardiovascular Science, Research department of Population Science and Experimental Medicine, Centre for Translational Genomics, 222 Euston Road, London, NW1 2DA, UK
| | - Desana Kocevska
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, 3000 CA, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, 3000 CA, The Netherlands
| | - Jessica Tyrrell
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Robin N Beaumont
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Melvyn Hillsdon
- Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, Exeter, EX1 2LU, UK
| | - Katherine S Ruth
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Marcus A Tuke
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Seth A Sharp
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Yingjie Ji
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Jamie W Harrison
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Rachel M Freathy
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Anna Murray
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Annemarie I Luik
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, 3000 CA, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, 3000 CA, The Netherlands
| | - Jacqueline M Lane
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02111, USA
- Departments of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 02115, USA
| | - Martin K Rutter
- Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, M13 9PL, UK
- Manchester Diabetes Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Oxford Road, 193 Hathersage Road, Manchester, M13 0JE, UK
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, 3000 CA, The Netherlands
- Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, MA, 02115, USA
| | - Zoltán Kutalik
- Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne, 1010, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - Meena Kumari
- ISER, University of Essex, Colchester, Essex, CO4 3SQ, UK
| | - Timothy M Frayling
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK
| | - Michael N Weedon
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK.
| | - Philip R Gehrman
- Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, 19104, PA, USA
- Perelman School of Medicine of the University of Pennsylvania, Philadelphia, 19104, PA, USA
| | - Andrew R Wood
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK.
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43
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The role of the circadian system in the etiology and pathophysiology of ADHD: time to redefine ADHD? ACTA ACUST UNITED AC 2019; 11:5-19. [DOI: 10.1007/s12402-018-0271-z] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 09/19/2018] [Indexed: 12/20/2022]
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44
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Dashti HS, Jones SE, Wood AR, Lane JM, van Hees VT, Wang H, Rhodes JA, Song Y, Patel K, Anderson SG, Beaumont RN, Bechtold DA, Bowden J, Cade BE, Garaulet M, Kyle SD, Little MA, Loudon AS, Luik AI, Scheer FAJL, Spiegelhalder K, Tyrrell J, Gottlieb DJ, Tiemeier H, Ray DW, Purcell SM, Frayling TM, Redline S, Lawlor DA, Rutter MK, Weedon MN, Saxena R. Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates. Nat Commun 2019; 10:1100. [PMID: 30846698 PMCID: PMC6405943 DOI: 10.1038/s41467-019-08917-4] [Citation(s) in RCA: 297] [Impact Index Per Article: 59.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 01/31/2019] [Indexed: 12/22/2022] Open
Abstract
Sleep is an essential state of decreased activity and alertness but molecular factors regulating sleep duration remain unknown. Through genome-wide association analysis in 446,118 adults of European ancestry from the UK Biobank, we identify 78 loci for self-reported habitual sleep duration (p < 5 × 10−8; 43 loci at p < 6 × 10−9). Replication is observed for PAX8, VRK2, and FBXL12/UBL5/PIN1 loci in the CHARGE study (n = 47,180; p < 6.3 × 10−4), and 55 signals show sign-concordant effects. The 78 loci further associate with accelerometer-derived sleep duration, daytime inactivity, sleep efficiency and number of sleep bouts in secondary analysis (n = 85,499). Loci are enriched for pathways including striatum and subpallium development, mechanosensory response, dopamine binding, synaptic neurotransmission and plasticity, among others. Genetic correlation indicates shared links with anthropometric, cognitive, metabolic, and psychiatric traits and two-sample Mendelian randomization highlights a bidirectional causal link with schizophrenia. This work provides insights into the genetic basis for inter-individual variation in sleep duration implicating multiple biological pathways. Sleep is essential for homeostasis and insufficient or excessive sleep are associated with adverse outcomes. Here, the authors perform GWAS for self-reported habitual sleep duration in adults, supported by accelerometer-derived measures, and identify genetic correlation with psychiatric and metabolic traits
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Affiliation(s)
- Hassan S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA.,Broad Institute, Cambridge, 02142, MA, USA
| | - Samuel E Jones
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, EX2 5DW, UK
| | - Andrew R Wood
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, EX2 5DW, UK
| | - Jacqueline M Lane
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA.,Broad Institute, Cambridge, 02142, MA, USA.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA
| | | | - Heming Wang
- Broad Institute, Cambridge, 02142, MA, USA.,Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, 02115, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, 02115, MA, USA
| | - Jessica A Rhodes
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA.,Broad Institute, Cambridge, 02142, MA, USA
| | - Yanwei Song
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA.,Northeastern University College of Science, 176 Mugar Life Sciences, 360 Huntington Avenue, Boston, MA, 02015, USA
| | - Krunal Patel
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA.,Northeastern University College of Science, 176 Mugar Life Sciences, 360 Huntington Avenue, Boston, MA, 02015, USA
| | - Simon G Anderson
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PL, UK
| | - Robin N Beaumont
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, EX2 5DW, UK
| | - David A Bechtold
- Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
| | - Jack Bowden
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, BS8 2BN, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Brian E Cade
- Broad Institute, Cambridge, 02142, MA, USA.,Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, 02115, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, 02115, MA, USA
| | - Marta Garaulet
- Department of Physiology, University of Murcia, Murcia, 30100, Spain.,IMIB-Arrixaca, Murcia, 30120, Spain
| | - Simon D Kyle
- Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 7LF, UK
| | - Max A Little
- Department of Mathematics, Aston University, Birmingham, B4 7ET, UK.,Media Lab, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA
| | - Andrew S Loudon
- Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
| | - Annemarie I Luik
- Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 7LF, UK
| | - Frank A J L Scheer
- Broad Institute, Cambridge, 02142, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, 02115, MA, USA.,Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, 02115, MA, USA
| | - Kai Spiegelhalder
- Clinic for Psychiatry and Psychotherapy, Medical Centre - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, 79106, Germany
| | - Jessica Tyrrell
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, EX2 5DW, UK
| | - Daniel J Gottlieb
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, 02115, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, 02115, MA, USA.,VA Boston Healthcare System, Boston, 02132, MA, USA
| | - Henning Tiemeier
- Deprtment of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, 02115, MA, USA.,Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015, The Netherlands
| | - David W Ray
- Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
| | - Shaun M Purcell
- Department of Psychiatry, Brigham & Women's Hospital, Harvard Medical School, 02115, Boston, MA, USA
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, EX2 5DW, UK
| | - Susan Redline
- Departments of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, 02115, MA, USA
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, BS8 2BN, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Martin K Rutter
- Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK.,Manchester Diabetes Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, M13 9PL, UK
| | - Michael N Weedon
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, EX2 5DW, UK
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA. .,Broad Institute, Cambridge, 02142, MA, USA. .,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA.
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45
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Dashti HS, Redline S, Saxena R. Polygenic risk score identifies associations between sleep duration and diseases determined from an electronic medical record biobank. Sleep 2019; 42:zsy247. [PMID: 30521049 PMCID: PMC6424085 DOI: 10.1093/sleep/zsy247] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 11/07/2018] [Accepted: 12/03/2018] [Indexed: 01/01/2023] Open
Abstract
STUDY OBJECTIVES We aimed to detect cross-sectional phenotype and polygenic risk score (PRS) associations between sleep duration and prevalent diseases using the Partners Biobank, a hospital-based cohort study linking electronic medical records (EMR) with genetic information. METHODS Disease prevalence was determined from EMR, and sleep duration was self-reported. A PRS for sleep duration was derived using 78 previously associated SNPs from genome-wide association studies (GWAS) for self-reported sleep duration. We tested for associations between (1) self-reported sleep duration and 22 prevalent diseases (n = 30 251), (2) the PRS and self-reported sleep duration (n = 6903), and (3) the PRS and the 22 prevalent diseases (n = 16 033). For observed PRS-disease associations, we tested causality using two-sample Mendelian randomization (MR). RESULTS In the age-, sex-, and race-adjusted model, U-shaped associations were observed for sleep duration and asthma, depression, hypertension, insomnia, obesity, obstructive sleep apnea, and type 2 diabetes, where both short and long sleepers had higher odds for these diseases than normal sleepers (p < 2.27 × 10-3). Next, we confirmed associations between the PRS and longer sleep duration (0.65 ± 0.19 SD minutes per effect allele; p = 7.32 × 10-04). The PRS collectively explained 1.4% of the phenotypic variance in sleep duration. After adjusting for age, sex, genotyping array, and principal components of ancestry, we observed that the PRS was also associated with congestive heart failure (CHF; p = 0.015), obesity (p = 0.019), hypertension (p = 0.039), restless legs syndrome (RLS; p = 0.041), and insomnia (p = 0.049). Associations were maintained following additional adjustment for obesity status, except for hypertension and insomnia. For all diseases, except RLS, carrying a higher genetic burden of the 78 sleep duration-increasing alleles (i.e. higher sleep duration PRS) associated with lower odds for prevalent disease. In MR, we estimated causal associations between genetically defined longer sleep duration with decreased risk of CHF (inverse variance weighted [IVW] OR per minute of sleep [95% CI] = 0.978 [0.961-0.996]; p = 0.019) and hypertension (IVW OR [95% CI] = 0.993 [0.986-1.000]; p = 0.049), and increased risk of RLS (IVW OR [95% CI] = 1.018 [1.000-1.036]; p = 0.045). CONCLUSIONS By validating the PRS for sleep duration and identifying cross-phenotype associations, we lay the groundwork for future investigations on the intersection between sleep, genetics, clinical measures, and diseases using large EMR datasets.
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Affiliation(s)
- Hassan S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Susan Redline
- Departments of Medicine, Brigham and Women’s Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA
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46
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Nishiyama T, Nakatochi M, Goto A, Iwasaki M, Hachiya T, Sutoh Y, Shimizu A, Wang C, Tanaka H, Watanabe M, Hosono A, Tamai Y, Yamada T, Yamaji T, Sawada N, Fukumoto K, Otsuka K, Tanno K, Tomita H, Kojima K, Nagasaki M, Hozawa A, Hishida A, Sasakabe T, Nishida Y, Hara M, Ito H, Oze I, Nakamura Y, Mikami H, Ibusuki R, Takezaki T, Koyama T, Kuriyama N, Endoh K, Kuriki K, Turin TC, Naoyuki T, Katsuura-Kamano S, Uemura H, Okada R, Kawai S, Naito M, Momozawa Y, Kubo M, Sasaki M, Yamamoto M, Tsugane S, Wakai K, Suzuki S. Genome-wide association meta-analysis and Mendelian randomization analysis confirm the influence of ALDH2 on sleep durationin the Japanese population. Sleep 2019; 42:5362027. [DOI: 10.1093/sleep/zsz046] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 02/20/2019] [Indexed: 11/14/2022] Open
Affiliation(s)
- Takeshi Nishiyama
- Department of Public Health, Nagoya City University Graduate School of Medicine, Nagoya, Japan
- Department of Public Health, Aichi Medical University School of Medicine, Nagakute, Japan
| | - Masahiro Nakatochi
- Data Science Division, Data Coordinating Center, Department of Advanced Medicine, Nagoya University Hospital, Japan
| | - Atsushi Goto
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Chaochen Wang
- Department of Public Health, Nagoya City University Graduate School of Medicine, Nagoya, Japan
- Department of Public Health, Aichi Medical University School of Medicine, Nagakute, Japan
| | - Hideo Tanaka
- Osaka Prefectural Kishiwada Public Health Center, Osaka, Japan
| | - Miki Watanabe
- Department of Public Health, Nagoya City University Graduate School of Medicine, Nagoya, Japan
| | - Akihiro Hosono
- Department of Public Health, Nagoya City University Graduate School of Medicine, Nagoya, Japan
| | - Yuya Tamai
- Department of Public Health, Nagoya City University Graduate School of Medicine, Nagoya, Japan
| | | | - Taiki Yamaji
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Norie Sawada
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Kentaro Fukumoto
- Department of Neuropsychiatry, School of Medicine, Iwate Medical University, Iwate, Japan
| | - Kotaro Otsuka
- Department of Neuropsychiatry, School of Medicine, Iwate Medical University, Iwate, Japan
- Division of Clinical Research and Epidemiology, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Kozo Tanno
- Division of Clinical Research and Epidemiology, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
- Department of Hygiene and Preventive Medicine, School of Medicine, Iwate Medical University, Iwate, Japan
| | - Hiroaki Tomita
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Kaname Kojima
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Masao Nagasaki
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Atsushi Hozawa
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Tae Sasakabe
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yuichiro Nishida
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
| | - Megumi Hara
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
| | - Hidemi Ito
- Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Isao Oze
- Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Yohko Nakamura
- Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan
| | - Haruo Mikami
- Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan
| | - Rie Ibusuki
- Department of International Islands and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Toshiro Takezaki
- Department of International Islands and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Teruhide Koyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine Graduate School of Medical Science, Kyoto, Japan
| | - Nagato Kuriyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine Graduate School of Medical Science, Kyoto, Japan
| | - Kaori Endoh
- Laboratory of Public Health, Graduate School of Integrated Pharmaceutical and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Kiyonori Kuriki
- Laboratory of Public Health, Graduate School of Integrated Pharmaceutical and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Tanvir C Turin
- Department of Health Science, Shiga University of Medical Science, Shiga, Japan
| | - Takashima Naoyuki
- Department of Health Science, Shiga University of Medical Science, Shiga, Japan
| | - Sakurako Katsuura-Kamano
- Department of Preventive Medicine, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
| | - Hirokazu Uemura
- Department of Preventive Medicine, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
| | - Rieko Okada
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sayo Kawai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Mariko Naito
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
- Department of Oral Epidemiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Michiaki Kubo
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
- Division of Ultra-High Field MRI and Department of Radiology, Iwate Medical University, Iwate, Japan
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Shoichiro Tsugane
- Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medicine, Nagoya, Japan
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Wang J, Kwok MK, Au Yeung SL, Li AM, Lam HS, Leung JYY, Hui LL, Leung GM, Schooling CM. Sleep duration and risk of diabetes: Observational and Mendelian randomization studies. Prev Med 2019; 119:24-30. [PMID: 30508554 DOI: 10.1016/j.ypmed.2018.11.019] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 11/27/2018] [Accepted: 11/30/2018] [Indexed: 10/27/2022]
Abstract
Inadequate sleep could contribute to type 2 diabetes, but observational studies are inconsistent and open to biases, particularly from confounding. We used Mendelian randomization (MR) to obtain an unconfounded estimate of the effect of sleep duration on diabetes, fasting glucose (FG) and hemoglobin A1c (HbA1c), and an observation study to assess differences by sex. Using MR, we assessed the effects of genetically instrumented sleep on diabetes, based on 68 single nucleotide polymorphisms (SNPs), applied to the DIAbetes Genetics Replication and meta-analysis case (n = 26,676)-control (n = 132,532) study and on FG and HbA1c, based on 55 SNPs, applied to the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) study of FG (n = 122,743) and HbA1c (n = 123,665). In the population-representative Hong Kong Chinese "Children of 1997" birth cohort we assessed whether associations of sleep duration at ~17.5 years with FG and HbA1c differed by sex. Using inverse variance weighting with multiplicative random effects, sleep duration was not associated with diabetes (odds ratio (OR) 0.85 per hour of sleep, 95% confidence interval (CI) 0.64 to 1.13), FG (-0.032 mmol/l per hour of sleep, 95% CI -0.126 to 0.063) or HbA1c (-0.022% per hour of sleep, 95% CI -0.069 to 0.024). In "Children of 1997", the associations of sleep duration with FG differed by sex (p for interaction 0.05) but not with HbA1c. Overall sleep duration does not appear to be related to diabetes, FG or HbA1c, but the possibility of sex differences merits investigation.
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Affiliation(s)
- Jiao Wang
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Man Ki Kwok
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Shiu Lun Au Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Albert Martin Li
- Department of Pediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Hugh Simon Lam
- Department of Pediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - June Yue Yan Leung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Lai Ling Hui
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Gabriel Matthew Leung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Catherine Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; CUNY School of Public Health and Health Policy, New York, USA.
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48
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Satterfield BC, Stucky B, Landolt HP, Van Dongen HP. Unraveling the genetic underpinnings of sleep deprivation-induced impairments in human cognition. PROGRESS IN BRAIN RESEARCH 2019; 246:127-158. [DOI: 10.1016/bs.pbr.2019.03.026] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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49
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Hedström AK, Bellocco R, Ye W, Trolle Lagerros Y, Åkerstedt T. Association Between Insomnia And Mortality Is Only Evident Among Long Sleepers. Nat Sci Sleep 2019; 11:333-342. [PMID: 32009823 PMCID: PMC6859119 DOI: 10.2147/nss.s222049] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Accepted: 10/07/2019] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Previous studies investigating the relationship between insomnia and mortality have been inconsistent. PURPOSE We aimed to assess whether nocturnal insomnia symptoms and non-restorative sleep are associated with all-cause mortality and whether they modify the associations between short and long sleep duration and all-cause mortality. PATIENTS AND METHODS The present report is based on a prospective cohort study of 39,139 participants with a mean follow-up time of 19.6 years. Cox proportional hazard models with attained age as timescale were used to estimate overall mortality hazard ratios (HRs) with 95% confidence intervals (CI) for different categories of sleep duration and insomnia symptoms. RESULTS Both difficulty initiating sleep and daytime sleepiness were independently associated with increased mortality among those with sleep duration of 9 hrs or more (HR 1.51, 95% CI 1.11-2.07 and HR 1.37, 95% CI 1.03-1.82). Mortality increased with increasing severity of difficulties initiating sleep (p for trend 0.04) and daytime sleepiness (p for trend 0.01) among the long sleepers. None of the insomnia symptoms were associated with mortality among those who reported sleep duration of 8 hrs or less. CONCLUSION Long sleep in combination with difficulties initiating sleep and daytime sleepiness, possibly due to psychiatric or physical disorders, was thus associated with increased mortality, whereas long sleep without difficulties falling asleep or daytime sleepiness was not associated with mortality. Our study emphasizes the need to take nocturnal insomnia symptoms and daytime sleepiness into consideration when assessing the influence of sleep duration on mortality. Additional research is needed to elucidate the relationship between long sleep, insomnia and related psychiatric and physical disorders.
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Affiliation(s)
- Anna Karin Hedström
- Department of Clinical Neuroscience and Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Rino Bellocco
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, and Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
| | - Weimin Ye
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ylva Trolle Lagerros
- Department of Medicine, Clinical Epidemiology Unit, Karolinska Institutet, Stockholm, Sweden, and Obesity Center, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Torbjörn Åkerstedt
- Stress Research, Stockholm University, Stockholm, Sweden, and Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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50
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Almoosawi S, Vingeliene S, Gachon F, Voortman T, Palla L, Johnston JD, Van Dam RM, Darimont C, Karagounis LG. Chronotype: Implications for Epidemiologic Studies on Chrono-Nutrition and Cardiometabolic Health. Adv Nutr 2019; 10:30-42. [PMID: 30500869 PMCID: PMC6370261 DOI: 10.1093/advances/nmy070] [Citation(s) in RCA: 105] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Accepted: 08/20/2018] [Indexed: 12/12/2022] Open
Abstract
Chrono-nutrition is an emerging research field in nutritional epidemiology that encompasses 3 dimensions of eating behavior: timing, frequency, and regularity. To date, few studies have investigated how an individual's circadian typology, i.e., one's chronotype, affects the association between chrono-nutrition and cardiometabolic health. This review sets the directions for future research by providing a narrative overview of recent epidemiologic research on chronotype, its determinants, and its association with dietary intake and cardiometabolic health. Limited research was found on the association between chronotype and dietary intake in infants, children, and older adults. Moreover, most of the evidence in adolescents and adults was restricted to cross-sectional surveys with few longitudinal cohorts simultaneously collecting data on chronotype and dietary intake. There was a gap in the research concerning the association between chronotype and the 3 dimensions of chrono-nutrition. Whether chronotype modifies the association between diet and cardiometabolic health outcomes remains to be elucidated. In conclusion, further research is required to understand the interplay between chronotype, chrono-nutrition, and cardiometabolic health outcomes.
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Affiliation(s)
- Suzana Almoosawi
- Brain, Performance, and Nutrition Research Center, Northumbria University, Newcastle-upon-Tyne, United Kingdom,Nestlé Research Center, Institute of Nutritional Sciences, Lausanne, Switzerland
| | - Snieguole Vingeliene
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Frederic Gachon
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland,Department of Diabetes and Circadian Rhythms, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Luigi Palla
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jonathan D Johnston
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Rob Martinus Van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Christian Darimont
- Nestlé Research Center, Institute of Nutritional Sciences, Lausanne, Switzerland
| | - Leonidas G Karagounis
- Nestlé Research Center, Institute of Nutritional Sciences, Lausanne, Switzerland,Nestlé Health Science, Vevey, Switzerland,Experimental Myology and Integrative Physiology Cluster, Plymouth Marjon University, Plymouth, United Kingdom,Address correspondence to LGK (e-mail: )
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