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Liu H, Li L, Zan X, Wei J. No bidirectional relationship between sleep phenotypes and risk of proliferative diabetic retinopathy: a two-sample Mendelian randomization study. Sci Rep 2024; 14:9585. [PMID: 38671284 PMCID: PMC11053118 DOI: 10.1038/s41598-024-60446-3] [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: 10/29/2023] [Accepted: 04/23/2024] [Indexed: 04/28/2024] Open
Abstract
This study aimed to investigate the probable existence of a causal relationship between sleep phenotypes and proliferative diabetic retinopathy (PDR). Single nucleotide polymorphisms associated with sleep phenotypes were selected as instrumental variables at the genome-wide significance threshold (P < 5 × 10-8). Inverse-variance weighted was applied as the primary Mendelian randomization (MR) analysis method, and MR Egger regression, weighted median, simple mode, and weighted mode methods were used as complementary analysis methods to estimate the causal association between sleep phenotypes and PDR. Results indicated that genetically predicted sleep phenotypes had no causal effects on PDR risk after Bonferroni correction (P = 0.05/10) [Chronotype: P = 0.143; Daytime napping: P = 0.691; Daytime sleepiness: P = 0.473; Insomnia: P = 0.181; Long sleep duration: P = 0.671; Morning person:P = 0.113; Short sleep duration: P = 0.517; Obstructive sleep apnea: P = 0.091; Sleep duration: P = 0.216; and snoring: P = 0.014]. Meanwhile, there are no reverse causality for genetically predicted PDR on sleep phenotypes [Chronotype: P = 0.100; Daytime napping: P = 0.146; Daytime sleepiness: P = 0.469; Insomnia: P = 0.571; Long sleep duration: P = 0.779; Morning person: P = 0.040; Short sleep duration: P = 0.875; Obstructive sleep apnea: P = 0.628; Sleep duration: P = 0.896; and snoring: P = 0.047]. This study's findings did not support the causal effect of between sleep phenotypes and PDR. Whereas, longitudinal studies can further verify results validation.
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Affiliation(s)
- Huan Liu
- Department of Ophthalmology, The First Affiliated Hospital of Henan University of Science and Technology, No. 24 Jinghua Road, Luoyang, 471003, Henan, People's Republic of China
| | - Lin Li
- Department of Ophthalmology, The First Affiliated Hospital of Henan University of Science and Technology, No. 24 Jinghua Road, Luoyang, 471003, Henan, People's Republic of China
| | - Xiaoning Zan
- Department of Ophthalmology, The First Affiliated Hospital of Henan University of Science and Technology, No. 24 Jinghua Road, Luoyang, 471003, Henan, People's Republic of China
| | - Jing Wei
- Department of Ophthalmology, The First Affiliated Hospital of Henan University of Science and Technology, No. 24 Jinghua Road, Luoyang, 471003, Henan, People's Republic of China.
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2
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Zheng JW, Ai SZ, Chang SH, Meng SQ, Shi L, Deng JH, Di TQ, Liu WY, Chang XW, Yue JL, Yang XQ, Zeng N, Bao YP, Sun Y, Lu L, Shi J. Association between alcohol consumption and sleep traits: observational and mendelian randomization studies in the UK biobank. Mol Psychiatry 2024; 29:838-846. [PMID: 38233469 DOI: 10.1038/s41380-023-02375-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 11/21/2023] [Accepted: 12/12/2023] [Indexed: 01/19/2024]
Abstract
Previous studies have shown that excessive alcohol consumption is associated with poor sleep. However, the health risks of light-to-moderate alcohol consumption in relation to sleep traits (e.g., insomnia, snoring, sleep duration and chronotype) remain undefined, and their causality is still unclear in the general population. To identify the association between alcohol consumption and multiple sleep traits using an observational and Mendelian randomization (MR) design. Observational analyses and one-sample MR (linear and nonlinear) were performed using clinical and individual-level genetic data from the UK Biobank (UKB). Two-sample MR was assessed using summary data from genome-wide association studies from the UKB and other external consortia. Phenotype analyses were externally validated using data from the National Health and Nutrition Examination Survey (2017-2018). Data analysis was conducted from January 2022 to October 2022. The association between alcohol consumption and six self-reported sleep traits (short sleep duration, long sleep duration, chronotype, snoring, waking up in the morning, and insomnia) were analysed. This study included 383,357 UKB participants (mean [SD] age, 57.0 [8.0] years; 46% male) who consumed a mean (SD) of 9.0 (10.0) standard drinks (one standard drink equivalent to 14 g of alcohol) per week. In the observational analyses, alcohol consumption was significantly associated with all sleep traits. Light-moderate-heavy alcohol consumption was linearly linked to snoring and the evening chronotype but nonlinearly associated with insomnia, sleep duration, and napping. In linear MR analyses, a 1-SD (14 g) increase in genetically predicted alcohol consumption was associated with a 1.14-fold (95% CI, 1.07-1.22) higher risk of snoring (P < 0.001), a 1.28-fold (95% CI, 1.20-1.37) higher risk of evening chronotype (P < 0.001) and a 1.24-fold (95% CI, 1.13-1.36) higher risk of difficulty waking up in the morning (P < 0.001). Nonlinear MR analyses did not reveal significant results after Bonferroni adjustment. The results of the two-sample MR analyses were consistent with those of the one-sample MR analyses, but with a slightly attenuated overall estimate. Our findings suggest that even low levels of alcohol consumption may affect sleep health, particularly by increasing the risk of snoring and evening chronotypes. The negative effects of alcohol consumption on sleep should be made clear to the public in order to promote public health.
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Affiliation(s)
- Jun-Wei Zheng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, 100191, Beijing, China
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, 100191, Beijing, China
| | - Si-Zhi Ai
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510182, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 511436, China
- Institute of Psycho-neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510120, China
| | - Su-Hua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), 100191, Beijing, China
| | - Shi-Qiu Meng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, 100191, Beijing, China
| | - Le Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), 100191, Beijing, China
| | - Jia-Hui Deng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), 100191, Beijing, China
| | - Tian-Qi Di
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, 100191, Beijing, China
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, 100191, Beijing, China
| | - Wang-Yue Liu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, 100191, Beijing, China
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, 100191, Beijing, China
| | - Xiang-Wen Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), 100191, Beijing, China
| | - Jing-Li Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), 100191, Beijing, China
| | - Xiao-Qin Yang
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, 100191, Beijing, China
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, 100191, Beijing, China
| | - Na Zeng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, 100191, Beijing, China
- School of Public Health, Peking University, 100191, Beijing, China
| | - Yan-Ping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, 100191, Beijing, China
| | - Yan Sun
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, 100191, Beijing, China.
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), 100191, Beijing, China.
- Peking-Tsinghua Center for Life Sciences and International Data Group/McGovern Institute for Brain Research, Peking University, 100191, Beijing, China.
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, 100191, Beijing, China.
- The State Key Laboratory of Natural and Biomimetic Drugs, Peking University, 100191, Beijing, China.
- The Key Laboratory for Neuroscience of the Ministry of Education and Health, Peking University, 100191, Beijing, China.
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3
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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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Larsen M, He F, Kawasawa YI, Berg A, Vgontzas AN, Liao D, Bixler EO, Fernandez-Mendoza J. Objective and subjective measures of sleep initiation are differentially associated with DNA methylation in adolescents. Clin Epigenetics 2023; 15:136. [PMID: 37634000 PMCID: PMC10464279 DOI: 10.1186/s13148-023-01553-2] [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: 01/19/2023] [Accepted: 08/14/2023] [Indexed: 08/28/2023] Open
Abstract
INTRODUCTION The onset of puberty is associated with a shift in the circadian timing of sleep, leading to delayed sleep initiation [i.e., later sleep onset time (SOT)] due to later bedtimes and/or longer sleep onset latency (SOL). Several genome-wide association studies (GWAS) have identified genes that may be involved in the etiology of sleep phenotypes. However, circadian rhythms are also epigenetically regulated; therefore, epigenetic biomarkers may provide insight into the physiology of the pubertal sleep onset shift and the pathophysiology of prolonged or delayed sleep initiation. RESULTS The gene-wide analysis indicated differential methylation within or around 1818 unique genes across the sleep initiation measurements using self-report, actigraphy (ACT), and polysomnography (PSG), while GWAS-informed analysis yielded 67 genes. Gene hits were identified for bedtime (PSG), SOL (subjective, ACT and PSG) and SOT (subjective and PSG). DNA methylation within 12 genes was associated with both subjective and PSG-measured SOL, 31 with both ACT- and PSG-measured SOL, 19 with both subjective and ACT-measured SOL, and one gene (SMG1P2) had methylation sites associated with subjective, ACT- and PSG-measured SOL. CONCLUSIONS Objective and subjective sleep initiation in adolescents is associated with altered DNA methylation in genes previously identified in adult GWAS of sleep and circadian phenotypes. Additionally, our data provide evidence for a potential epigenetic link between habitual (subjective and ACT) SOL and in-lab SOT and DNA methylation in and around genes involved in circadian regulation (i.e., RASD1, RAI1), cardiometabolic disorders (i.e., FADS1, WNK1, SLC5A6), and neuropsychiatric disorders (i.e., PRR7, SDK1, FAM172A). If validated, these sites may provide valuable targets for early detection and prevention of disorders involving prolonged or delayed SOT, such as insomnia, delayed sleep phase, and their comorbidity.
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Affiliation(s)
- Michael Larsen
- Sleep Research and Treatment Center, Department of Psychiatry & Behavioral Health, The Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Fan He
- Department of Public Health Sciences, The Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Yuka Imamura Kawasawa
- Departments of Biochemistry and Molecular Biology and Pharmacology, Institute for Personalized Medicine, The Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Arthur Berg
- Department of Public Health Sciences, The Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Alexandros N Vgontzas
- Sleep Research and Treatment Center, Department of Psychiatry & Behavioral Health, The Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Duanping Liao
- Department of Public Health Sciences, The Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Edward O Bixler
- Sleep Research and Treatment Center, Department of Psychiatry & Behavioral Health, The Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Julio Fernandez-Mendoza
- Sleep Research and Treatment Center, Department of Psychiatry & Behavioral Health, The Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA.
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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: 56] [Impact Index Per Article: 56.0] [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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6
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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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Abstract
The ALDH2*2 missense variant that commonly causes alcohol flushing reactions is the single genetic polymorphism associated with the largest number of traits in humans. The dysfunctional ALDH2 variant affects nearly 8% of the world population and is highly concentrated among East Asians. Carriers of the ALDH2*2 variant commonly present alterations in a number of blood biomarkers, clinical measurements, biometrics, drug prescriptions, dietary habits and lifestyle behaviors, and they are also more susceptible to aldehyde-associated diseases, such as cancer and cardiovascular disease. However, the interaction between alcohol and ALDH2-related pathology is not clearly delineated. Furthermore, genetic evidence indicates that the ALDH2*2 variant has been favorably selected for in the past 2000-3000 years. It is therefore necessary to consider the disease risk and mechanism associated with ALDH2 deficiency, and to understand the possible beneficial or protective effect conferred by ALDH2 deficiency and whether the pleiotropic effects of ALDH2 variance are all mediated by alcohol use.
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Affiliation(s)
- Che-Hong Chen
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | - Daria Mochly-Rosen
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
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8
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Yi M, Tan Y, Pi Y, Zhou Y, Fei Q, Zhao W, Zhang Y. Variants of candidate genes associated with the risk of obstructive sleep apnea. Eur J Clin Invest 2022; 52:e13673. [PMID: 34435353 DOI: 10.1111/eci.13673] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/16/2021] [Accepted: 08/24/2021] [Indexed: 12/22/2022]
Abstract
BACKGROUND The researches on the associations between different candidate genes and obstructive sleep apnea (OSA) are inconsistent. Here, we performed a comprehensive qualitative and quantitative analysis to estimate the contribution of variants from candidate genes to the risk of OSA. METHODS Qualitative analysis was conducted to find the relationships for all included genes. Then, quantitative analysis of both allele models and genotype models was applied to evaluate the risk variants for OSA. Furthermore, a similar analysis was performed in different ethnic groups. RESULTS We included 152 publications containing 75 genes for qualitative analysis. Among them, we included 93 articles containing 28 variants from 16 genes for quantitative analysis. Through allele models, we found 10 risk variants for OSA (rs1801133 of MTHFR, ɛ4 of ApoE, -1438G/A of 5-HT2A, -308G/A of TNF-α, Pro1019Pro of LEPR, rs1130864 and rs2794521 of CRP, D/I of ACE, LPR and VNTR of 5-HTT) with the ORs of 1.21-2.07 in global population. We found that the variant of ɛ2 of ApoE could uniquely decrease the risk of OSA in the East Asian subgroup, while the other 6 variants, including ɛ4 in ApoE, -308G/A in TNF-α, Pro1019Pro in LEPR, D/I in ACE, LPR and VNTR in 5-HTT, could increase the risk of OSA. As for the European subpopulation, we only found that -308G/A in TNF-α could increase the risk for OSA. CONCLUSIONS Eleven variants from the candidate genes are associated with the risk of OSA, which also show ethnicity differences in East Asian and European subgroups.
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Affiliation(s)
- Minhan Yi
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China.,School of Life Sciences, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Yun Tan
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China.,School of Life Sciences, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Yuze Pi
- School of Life Sciences, Central South University, Changsha, China
| | - Yicen Zhou
- School of Life Sciences, Central South University, Changsha, China
| | - Quanming Fei
- Xiangya Medical School, Central South University, Changsha, China
| | - Wangcheng Zhao
- Xiangya Medical School, Central South University, Changsha, China
| | - Yuan Zhang
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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9
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Treur JL, Munafò MR, Logtenberg E, Wiers RW, Verweij KJH. Using Mendelian randomization analysis to better understand the relationship between mental health and substance use: a systematic review. Psychol Med 2021; 51:1593-1624. [PMID: 34030749 PMCID: PMC8327626 DOI: 10.1017/s003329172100180x] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 04/17/2021] [Accepted: 04/21/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND Poor mental health has consistently been associated with substance use (smoking, alcohol drinking, cannabis use, and consumption of caffeinated drinks). To properly inform public health policy it is crucial to understand the mechanisms underlying these associations, and most importantly, whether or not they are causal. METHODS In this pre-registered systematic review, we assessed the evidence for causal relationships between mental health and substance use from Mendelian randomization (MR) studies, following PRISMA. We rated the quality of included studies using a scoring system that incorporates important indices of quality, such as the quality of phenotype measurement, instrument strength, and use of sensitivity methods. RESULTS Sixty-three studies were included for qualitative synthesis. The final quality rating was '-' for 16 studies, '- +' for 37 studies, and '+'for 10 studies. There was robust evidence that higher educational attainment decreases smoking and that there is a bi-directional, increasing relationship between smoking and (symptoms of) mental disorders. Another robust finding was that higher educational attainment increases alcohol use frequency, but decreases binge-drinking and alcohol use problems, and that mental disorders causally lead to more alcohol drinking without evidence for the reverse. CONCLUSIONS The current MR literature increases our understanding of the relationship between mental health and substance use. Bi-directional causal relationships are indicated, especially for smoking, providing further incentive to strengthen public health efforts to decrease substance use. Future MR studies should make use of large(r) samples in combination with detailed phenotypes, a wide range of sensitivity methods, and triangulate with other research methods.
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Affiliation(s)
- Jorien L. Treur
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
- Addiction Development and Psychopathology (ADAPT) Lab, Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
| | - Marcus R. Munafò
- School of Psychological Science, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, the University of Bristol, Bristol, UK
| | - Emma Logtenberg
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Reinout W. Wiers
- Addiction Development and Psychopathology (ADAPT) Lab, Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
- Center for Urban Mental Health, University of Amsterdam, Amsterdam, the Netherlands
| | - Karin J. H. Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
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10
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Abstract
This review summarizes the available data about genetic factors which can link ischemic stroke and sleep. Sleep patterns (subjective and objective measures) are characterized by heritability and comprise up to 38-46%. According to Mendelian randomization analysis, genetic liability for short sleep duration and frequent insomnia symptoms is associated with ischemic stroke (predominantly of large artery subtype). The potential genetic links include variants of circadian genes, genes encoding components of neurotransmitter systems, common cardiovascular risk factors, as well as specific genetic factors related to certain sleep disorders.
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Affiliation(s)
- Lyudmila Korostovtseva
- Sleep Laboratory, Research Department for Hypertension, Department for Cardiology, Almazov National Medical Research Centre, 2 Akkuratov Str., Saint Petersburg, 197341, Russia.
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11
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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: 32] [Impact Index Per Article: 10.7] [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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12
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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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13
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Takeuchi K, Naito M, Kawai S, Tsukamoto M, Kadomatsu Y, Kubo Y, Okada R, Nagayoshi M, Tamura T, Hishida A, Nakatochi M, Sasakabe T, Hashimoto S, Eguchi H, Momozawa Y, Ikezaki H, Murata M, Furusyo N, Tanaka K, Hara M, Nishida Y, Matsuo K, Ito H, Oze I, Mikami H, Nakamura Y, Kusakabe M, Takezaki T, Ibusuki R, Shimoshikiryo I, Suzuki S, Nishiyama T, Watanabe M, Koyama T, Ozaki E, Watanabe I, Kuriki K, Kita Y, Ueshima H, Matsui K, Arisawa K, Uemura H, Katsuura-Kamano S, Nakamura S, Narimatsu H, Hamajima N, Tanaka H, Wakai K. Study profile of the Japan Multi-institutional Collaborative Cohort (J-MICC) Study. J Epidemiol 2020; 31:660-668. [PMID: 32963210 PMCID: PMC8593573 DOI: 10.2188/jea.je20200147] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The Japan Multi-institutional Collaborative Cohort (J-MICC) study was launched in 2005 to examine gene-environment interactions in lifestyle-related diseases, including cancers, among the Japanese. This report describes the study design and baseline profile of the study participants. METHODS The participants of the J-MICC Study were individuals aged 35 to 69 years enrolled from respondents to study announcements in specified regions, inhabitants attending health checkup examinations provided by local governments, visitors at health checkup centers, and first-visit patients at a cancer hospital in Japan. At the time of the baseline survey, from 2005 to 2014, we obtained comprehensive information regarding demographics, education, alcohol consumption, smoking, sleeping, exercise, food intake frequency, medication and supplement use, personal and family disease history, psychological stress, and female reproductive history, and collected peripheral blood samples. RESULTS The baseline survey included 92,610 adults (mean age: 55.2 [9.4] years, 44.1% men) from 14 study regions in 12 prefectures. The participation rate was 33.5%, with participation ranging from 19.7% to 69.8% in different study regions. The largest number of participants was in the age groups of 65-69 years for men and 60-64 years for women. There were differences in body mass index, educational attainment, alcohol consumption, smoking, and sleep duration between men and women. CONCLUSIONS The J-MICC Study collected lifestyle and clinical data and biospecimens from over 90,000 participants. This cohort is expected to be a valuable resource for the national and international scientific community in providing evidence to support longer healthy lives.
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Affiliation(s)
- Kenji Takeuchi
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Mariko Naito
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine.,Department of Oral Epidemiology, Hiroshima University Graduate School of Biomedical and Health Sciences
| | - Sayo Kawai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine.,Department of Public Health, Aichi Medical University School of Medicine
| | - Mineko Tsukamoto
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Yuka Kadomatsu
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Yoko Kubo
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Rieko Okada
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Mako Nagayoshi
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Takashi Tamura
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine
| | - Tae Sasakabe
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine.,Department of Public Health, Aichi Medical University School of Medicine
| | - Shuji Hashimoto
- Department of Hygiene, Fujita Health University School of Medicine
| | - Hidetaka Eguchi
- Diagnosis and Therapeutics of Intractable Diseases and Intractable Disease Research Center, Juntendo University Graduate School of Medicine
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences
| | - Hiroaki Ikezaki
- Department of Comprehensive General Internal Medicine, Kyushu University Graduate School, Faculty of Medical Sciences.,Department of General Internal Medicine, Kyushu University Hospital
| | - Masayuki Murata
- Department of General Internal Medicine, Kyushu University Hospital
| | - Norihiro Furusyo
- Department of Environmental Medicine and Infectious Diseases, Kyushu University Graduate School of Medical Sciences
| | - Keitaro Tanaka
- Department of Preventive Medicine, Faculty of Medicine, Saga University
| | - Megumi Hara
- Department of Preventive Medicine, Faculty of Medicine, Saga University
| | - Yuichiro Nishida
- Department of Preventive Medicine, Faculty of Medicine, Saga University
| | - Keitaro Matsuo
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute.,Department of Cancer Epidemiology, Nagoya University Graduate School of Medicine
| | - Hidemi Ito
- Division of Cancer Information and Control, Aichi Cancer Center Research Institute.,Department of Descriptive Cancer Epidemiology, Nagoya University Graduate School of Medicine
| | - Isao Oze
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute
| | - Haruo Mikami
- Cancer Prevention Center, Chiba Cancer Center Research Institute
| | - Yohko Nakamura
- Cancer Prevention Center, Chiba Cancer Center Research Institute
| | - Miho Kusakabe
- Cancer Prevention Center, Chiba Cancer Center Research Institute
| | - Toshiro Takezaki
- Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences
| | - Rie Ibusuki
- Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences
| | - Ippei Shimoshikiryo
- Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences
| | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences
| | - Takeshi Nishiyama
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences
| | - Miki Watanabe
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences
| | - Teruhide Koyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine
| | - Etsuko Ozaki
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine
| | - Isao Watanabe
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine
| | - Kiyonori Kuriki
- Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka
| | | | - Hirotsugu Ueshima
- Center for Epidemiologic Research in Asia, Shiga University of Medical Science
| | - Kenji Matsui
- Division of Bioethics and Healthcare Law, The National Cancer Center Japan
| | - Kokichi Arisawa
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences
| | - Hirokazu Uemura
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences.,College of Nursing Art and Science, University of Hyogo
| | | | - Sho Nakamura
- Cancer Prevention and Control Division, Kanagawa Cancer Center Research Institute.,School of Health of Innovation, Kanagawa University of Human Services
| | - Hiroto Narimatsu
- Cancer Prevention and Control Division, Kanagawa Cancer Center Research Institute.,School of Health of Innovation, Kanagawa University of Human Services
| | - Nobuyuki Hamajima
- Department of Healthcare Administration, Nagoya University Graduate School of Medicine
| | | | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
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14
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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: 3] [Impact Index Per Article: 0.8] [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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15
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Twin studies of subjective sleep quality and sleep duration, and their behavioral correlates: Systematic review and meta-analysis of heritability estimates. Neurosci Biobehav Rev 2020; 109:78-89. [DOI: 10.1016/j.neubiorev.2019.12.028] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Revised: 12/04/2019] [Accepted: 12/23/2019] [Indexed: 12/28/2022]
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16
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Jia H, Nogawa S, Kawafune K, Hachiya T, Takahashi S, Igarashi M, Saito K, Kato H. GWAS of habitual coffee consumption reveals a sex difference in the genetic effect of the 12q24 locus in the Japanese population. BMC Genet 2019; 20:61. [PMID: 31345160 PMCID: PMC6659273 DOI: 10.1186/s12863-019-0763-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 07/08/2019] [Indexed: 01/04/2023] Open
Abstract
Background Studies on genetic effects of coffee consumption are scarce for Asian populations. We conducted a genome-wide association study (GWAS) of habitual coffee consumption in Japan using a self-reporting online survey. Results Candidate genetic loci associated with habitual coffee consumption were searched within a discovery cohort (N = 6,264) and confirmed in a replication cohort (N = 5,975). Two loci achieved genome-wide significance (P < 5 × 10− 8) in a meta-analysis of the discovery and replication cohorts: an Asian population-specific 12q24 (rs79105258; P = 9.5 × 10− 15), which harbors CUX2, and 7p21 (rs10252701; P = 1.0 × 10− 14), in the upstream region of the aryl hydrocarbon receptor (AHR) gene, involved in caffeine metabolism. Subgroup analysis revealed a stronger genetic effect of the 12q24 locus in males (P for interaction = 8.2 × 10− 5). Further, rs79105258 at the 12q24 locus exerted pleiotropic effects on body mass index (P = 3.5 × 10− 4) and serum triglyceride levels (P = 8.7 × 10− 3). Conclusions Our results consolidate the association of habitual coffee consumption with the 12q24 and 7p21 loci. The different effects of the 12q24 locus between males and females are a novel finding that improves our understanding of genetic influences on habitual coffee consumption. Electronic supplementary material The online version of this article (10.1186/s12863-019-0763-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Huijuan Jia
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
| | - Shun Nogawa
- Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan
| | - Kaoru Kawafune
- Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan
| | - Tsuyoshi Hachiya
- Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan.,Genome Analytics Japan Inc., 15-1-3205, Tomihisa-cho, Shinjuku-ku, Tokyo, 162-0067, Japan
| | - Shoko Takahashi
- Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan
| | - Maki Igarashi
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.,Department of Molecular Endocrinology, National Research Institute for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan
| | - Kenji Saito
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.,Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan
| | - Hisanori Kato
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
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