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Liu Y, Wang Y, Qin S, Jin X, Jin L, Gu W, Mu Y. Insights Into Genome-Wide Association Study for Diabetes: A Bibliometric and Visual Analysis From 2001 to 2021. Front Endocrinol (Lausanne) 2022; 13:817620. [PMID: 35360064 PMCID: PMC8963272 DOI: 10.3389/fendo.2022.817620] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/07/2022] [Indexed: 12/24/2022] Open
Abstract
Hundreds of research and review articles concerning genome-wide association study (GWAS) in diabetes have been published in the last two decades. We aimed to evaluate the hotspots and future trends in GWAS in diabetes research through bibliometric analysis. Accordingly, 567 research and review articles published between 2001 and 2021 were included. A rising trend was noted in the annual number of publications and citations on GWAS in diabetes during this period. Harvard University and Harvard Medical School have played leading roles in genome research. Hotspot analyses indicated that DNA methylation and genetic variation, especially in type 2 diabetes mellitus, are likely to remain the research hotspots. Moreover, the identification of genetic phenotypes associated with adiposity, metabolic memory, pancreatic islet, and inflammation is the leading trend in this research field. Through this review, we provide predictions on the main research trends in the future so as to shed light on new directions and ideas for further investigations on the genetic etiology of diabetes for its prevention and treatment.
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Affiliation(s)
- Yang Liu
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
- Department of Endocrinology, the Eighth Medical Center of People’s Liberation Army (PLA) General Hospital, Beijing, China
| | - Yun Wang
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
| | - Shan Qin
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
| | - Xinye Jin
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
- Department of Nephrology, Hainan Hospital of Chinese People’s Liberation Army (PLA) General Hospital, Academician Chen Xiangmei of Hainan Province Kidney Diseases Research Team Innovation Center, Sanya, China
| | - Lingzi Jin
- Department of International Medical Services, Peking Union Medical College Hospital, Beijing, China
| | - Weijun Gu
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
| | - Yiming Mu
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
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Manoogian ENC, Chow LS, Taub PR, Laferrère B, Panda S. Time-restricted Eating for the Prevention and Management of Metabolic Diseases. Endocr Rev 2022; 43:405-436. [PMID: 34550357 PMCID: PMC8905332 DOI: 10.1210/endrev/bnab027] [Citation(s) in RCA: 178] [Impact Index Per Article: 59.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Indexed: 02/08/2023]
Abstract
Time-restricted feeding (TRF, animal-based studies) and time-restricted eating (TRE, humans) are an emerging behavioral intervention approach based on the understanding of the role of circadian rhythms in physiology and metabolism. In this approach, all calorie intake is restricted within a consistent interval of less than 12 hours without overtly attempting to reduce calories. This article will summarize the origin of TRF/TRE starting with concept of circadian rhythms and the role of chronic circadian rhythm disruption in increasing the risk for chronic metabolic diseases. Circadian rhythms are usually perceived as the sleep-wake cycle and dependent rhythms arising from the central nervous system. However, the recent discovery of circadian rhythms in peripheral organs and the plasticity of these rhythms in response to changes in nutrition availability raised the possibility that adopting a consistent daily short window of feeding can sustain robust circadian rhythm. Preclinical animal studies have demonstrated proof of concept and identified potential mechanisms driving TRF-related benefits. Pilot human intervention studies have reported promising results in reducing the risk for obesity, diabetes, and cardiovascular diseases. Epidemiological studies have indicated that maintaining a consistent long overnight fast, which is similar to TRE, can significantly reduce risks for chronic diseases. Despite these early successes, more clinical and mechanistic studies are needed to implement TRE alone or as adjuvant lifestyle intervention for the prevention and management of chronic metabolic diseases.
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Affiliation(s)
| | - Lisa S Chow
- University of Minnesota, Division of Diabetes, Endocrinology and Metabolism, Minneapolis, Minnesota 55455, USA
| | - Pam R Taub
- University of California, San Diego, Division of Cardiovascular Diseases, Department of Medicine, 9434 Medical Center Drive, La Jolla, California 92037, USA
| | - Blandine Laferrère
- New York Nutrition Obesity Research Center, Division of Endocrinology, Department of Medicine, Columbia University Irving Medical Center; New York, New York 10032, USA
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Balkhiyarova Z, Luciano R, Kaakinen M, Ulrich A, Shmeliov A, Bianchi M, Chioma L, Dallapiccola B, Prokopenko I, Manco M. Relationship between glucose homeostasis and obesity in early life-a study of Italian children and adolescents. Hum Mol Genet 2022; 31:816-826. [PMID: 34590674 PMCID: PMC8895752 DOI: 10.1093/hmg/ddab287] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 09/15/2021] [Accepted: 09/16/2021] [Indexed: 01/09/2023] Open
Abstract
Epidemic obesity is the most important risk factor for prediabetes and type 2 diabetes (T2D) in youth as it is in adults. Obesity shares pathophysiological mechanisms with T2D and is likely to share part of the genetic background. We aimed to test if weighted genetic risk scores (GRSs) for T2D, fasting glucose (FG) and fasting insulin (FI) predict glycaemic traits and if there is a causal relationship between obesity and impaired glucose metabolism in children and adolescents. Genotyping of 42 SNPs established by genome-wide association studies for T2D, FG and FI was performed in 1660 Italian youths aged between 2 and 19 years. We defined GRS for T2D, FG and FI and tested their effects on glycaemic traits, including FG, FI, indices of insulin resistance/beta cell function and body mass index (BMI). We evaluated causal relationships between obesity and FG/FI using one-sample Mendelian randomization analyses in both directions. GRS-FG was associated with FG (beta = 0.075 mmol/l, SE = 0.011, P = 1.58 × 10-11) and beta cell function (beta = -0.041, SE = 0.0090 P = 5.13 × 10-6). GRS-T2D also demonstrated an association with beta cell function (beta = -0.020, SE = 0.021 P = 0.030). We detected a causal effect of increased BMI on levels of FI in Italian youths (beta = 0.31 ln (pmol/l), 95%CI [0.078, 0.54], P = 0.0085), while there was no effect of FG/FI levels on BMI. Our results demonstrate that the glycaemic and T2D risk genetic variants contribute to higher FG and FI levels and decreased beta cell function in children and adolescents. The causal effects of adiposity on increased insulin resistance are detectable from childhood age.
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Affiliation(s)
- Zhanna Balkhiyarova
- Section of Statistical Multi-Omics, Department of Clinical and Experimental Medicine, University of Surrey, Guildford GU2 7XH, UK
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre Russian Academy of Sciences, Ufa 450008, Russian Federation
- Department of Endocrinology, Bashkir State Medical University, Ufa 450054, Russian Federation
| | - Rosa Luciano
- Research Area for Multifactorial Disease, Bambino Gesù Children’s Hospital, IRCCS, Rome 00146, Italy
- Department of Laboratory Medicine, Bambino Gesù Children’s Hospital, IRCCS, Rome 00146, Italy
| | - Marika Kaakinen
- Section of Statistical Multi-Omics, Department of Clinical and Experimental Medicine, University of Surrey, Guildford GU2 7XH, UK
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK
| | - Anna Ulrich
- Section of Statistical Multi-Omics, Department of Clinical and Experimental Medicine, University of Surrey, Guildford GU2 7XH, UK
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK
| | - Aleksey Shmeliov
- Section of Statistical Multi-Omics, Department of Clinical and Experimental Medicine, University of Surrey, Guildford GU2 7XH, UK
| | - Marzia Bianchi
- Research Area for Multifactorial Disease, Bambino Gesù Children’s Hospital, IRCCS, Rome 00146, Italy
| | - Laura Chioma
- Unit of Endocrinology, Bambino Gesù Children's Hospital, IRCCS, Rome 00146, Italy
| | - Bruno Dallapiccola
- Genetics and Rare Diseases Research Division, Bambino Gesù Children's Hospital, IRCCS, Rome 00146, Italy
| | - Inga Prokopenko
- Section of Statistical Multi-Omics, Department of Clinical and Experimental Medicine, University of Surrey, Guildford GU2 7XH, UK
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre Russian Academy of Sciences, Ufa 450008, Russian Federation
- UMR 8199—EGID, Institut Pasteur de Lille, CNRS, University of Lille, Lille 59000, France
| | - Melania Manco
- Research Area for Multifactorial Disease, Bambino Gesù Children’s Hospital, IRCCS, Rome 00146, Italy
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Downie CG, Dimos SF, Bien SA, Hu Y, Darst BF, Polfus LM, Wang Y, Wojcik GL, Tao R, Raffield LM, Armstrong ND, Polikowsky HG, Below JE, Correa A, Irvin MR, Rasmussen-Torvik LJF, Carlson CS, Phillips LS, Liu S, Pankow JS, Rich SS, Rotter JI, Buyske S, Matise TC, North KE, Avery CL, Haiman CA, Loos RJF, Kooperberg C, Graff M, Highland HM. Multi-ethnic GWAS and fine-mapping of glycaemic traits identify novel loci in the PAGE Study. Diabetologia 2022; 65:477-489. [PMID: 34951656 PMCID: PMC8810722 DOI: 10.1007/s00125-021-05635-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 10/21/2021] [Indexed: 01/02/2023]
Abstract
AIMS/HYPOTHESIS Type 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study. METHODS We conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci. RESULTS Four novel associations were identified (p < 5 × 10-9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis. CONCLUSIONS/INTERPRETATION Our findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations. DATA AVAILABILITY Full summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog ( https://www.ebi.ac.uk/gwas/downloads/summary-statistics ).
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Affiliation(s)
- Carolina G Downie
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Sofia F Dimos
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Stephanie A Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Yao Hu
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Burcu F Darst
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Linda M Polfus
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
- Ambry Genetics, Aliso Viejo, CA, USA
| | - Yujie Wang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Genevieve L Wojcik
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nicole D Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hannah G Polikowsky
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jennifer E Below
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adolfo Correa
- Department of Medicine, Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Laura J F Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Christopher S Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lawrence S Phillips
- Atlanta VA Medical Center, Decatur, GA, USA
- Department of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA, USA
| | - Simin Liu
- Department of Medicine, Division of Endocrinology, Warren Alpert School of Medicine, Brown University, Providence, RI, USA
- Department of Epidemiology, Brown School of Public Health, Providence, RI, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- Department of Pediatrics, Genome Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Steven Buyske
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
| | - Tara C Matise
- Department of Genetics, Rutgers University, Piscataway, NJ, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christy L Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Xue P, Tan X, Wu J, Tang X, Benedict C. No association between a common type 2 diabetes risk gene variant in the melatonin receptor gene (MTNR1B) and mortality among type 2 diabetes patients. J Pineal Res 2022; 72:e12785. [PMID: 34967052 DOI: 10.1111/jpi.12785] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 12/15/2021] [Accepted: 12/27/2021] [Indexed: 02/05/2023]
Abstract
The minor G risk allele in the common melatonin receptor gene (MTNR1B, rs10830963) has been associated with an increased risk of myocardial infarction among patients with type 2 diabetes (T2D). Furthermore, activating the melatonin receptor 1B through melatonin has been shown to promote cell proliferation, which could be hypothesized to increase cancer risk. Cardiovascular disease (CVD) and cancer are common causes of death among patients with T2D. Using data from 14 736 patients with T2D who participated in the UK Biobank investigation, we hypothesized an additive effect of the G risk allele on all-cause mortality, CVD mortality, and cancer mortality. As shown by Cox regression adjusted for confounders such as age, glucose-lowering medication, and socioeconomic status, no significant trend between the number of G risk alleles and mortality outcomes was found during the follow-up period of 11.1 years. Our negative findings do not speak against the role of this gene variant in the development of T2D, as repeatedly shown by previous large-scale studies. Instead, they may suggest that rs10830963 is less relevant for mortality risk in patients with T2D.
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Affiliation(s)
- Pei Xue
- Department of Surgical Sciences, Sleep Science Laboratory (BMC), Uppsala University, Uppsala, Sweden
- Sleep Medicine Center, Department of Respiratory and Critical Care Medicine, Mental Health Center, Translational Neuroscience Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Xiao Tan
- Department of Surgical Sciences, Sleep Science Laboratory (BMC), Uppsala University, Uppsala, Sweden
| | - Jiafei Wu
- Department of Surgical Sciences, Sleep Science Laboratory (BMC), Uppsala University, Uppsala, Sweden
| | - Xiangdong Tang
- Sleep Medicine Center, Department of Respiratory and Critical Care Medicine, Mental Health Center, Translational Neuroscience Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Christian Benedict
- Department of Surgical Sciences, Sleep Science Laboratory (BMC), Uppsala University, Uppsala, Sweden
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van Poppel MNM, Corcoy R, Hill D, Simmons D, Mendizabal L, Zulueta M, Simon L, Desoye G. Interaction between rs10830962 polymorphism in MTNR1B and lifestyle intervention on maternal and neonatal outcomes: secondary analyses of the DALI lifestyle randomized controlled trial. Am J Clin Nutr 2022; 115:388-396. [PMID: 34669935 DOI: 10.1093/ajcn/nqab347] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 10/12/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Interactions between polymorphisms of the melatonin receptor 1B (MTNR1B) gene and lifestyle intervention for gestational diabetes have been described. Whether these are specific for physical activity or the healthy eating intervention is unknown. OBJECTIVES The aim was to assess the interaction between MTNR1B rs10830962 and rs10830963 polymorphisms and lifestyle interventions during pregnancy. METHODS Women with a BMI (in kg/m2) of ≥29 (n = 436) received counseling on healthy eating (HE), physical activity (PA), or both. The control group received usual care. This secondary analysis had a factorial design with comparison of HE compared with no HE and PA compared with no PA. Maternal outcomes at 24-28 wk were gestational weight gain (GWG), maternal fasting glucose, insulin, insulin resistance (HOMA-IR), disposition index, and development of GDM. Neonatal outcomes were cord blood leptin and C-peptide and estimated neonatal fat percentage. The interaction between receiving either the HE or PA intervention and genotypes of both rs10830962 and rs10830963 was assessed using multilevel regression analysis. RESULTS GDM risk was increased in women homozygous for the G allele of rs10830962 (OR: 2.60; 95% CI: 1.34, 5.06) or rs10830963 (OR: 2.83; 95% CI: 1.24, 6.47). Significant interactions between rs10830962 and interventions were found: in women homozygous for the G allele but not in the other genotypes, the PA intervention reduced maternal fasting insulin (β: -0.16; 95% CI: -0.33, 0.02; P = 0.08) and HOMA-IR (β: -0.17; 95% CI: -0.35, 0.01; P = 0.06), and reduced cord blood leptin (β: -0.84; 95% CI: -1.42, -0.25; P = 0.01) and C-peptide (β: -0.62; 95% CI: -1.07, -0.17; P = 0.01). In heterozygous women, the HE intervention had no effect, whereas in women homozygous for the C allele, HE intervention reduced GWG (β: -1.6 kg; 95% CI: -2.4, -0.8 kg). No interactions were found. CONCLUSIONS In women homozygous for the risk allele of MTNR1B rs10830962, GDM risk was increased and PA intervention might be more beneficial than HE intervention for reducing maternal insulin resistance, cord blood C-peptide, and cord blood leptin.
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Affiliation(s)
| | - Rosa Corcoy
- Institut de Recerca de l´Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.,CIBER Bioengineering, Biomaterials and Nanotechnology, Instituto de Salud Carlos III, Madrid, Spain
| | - David Hill
- Recherche en Santé Lawson SA, Bronschhofen, Switzerland.,Lawson Health Research Institute, London, Ontario, Canada
| | - David Simmons
- Western Sydney University, Campbelltown, New South Wales, Australia.,Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | | | | | - Laureano Simon
- Department of Obstetrics and Gynecology, Medical University Graz, Graz, Austria
| | - Gernot Desoye
- Department of Obstetrics and Gynecology, Medical University Graz, Graz, Austria
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Interactions between nocturnal melatonin secretion, metabolism, and sleeping behavior in adolescents with obesity. Int J Obes (Lond) 2022; 46:1051-1058. [PMID: 35140394 PMCID: PMC9050511 DOI: 10.1038/s41366-022-01077-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Revised: 12/17/2021] [Accepted: 01/12/2022] [Indexed: 02/06/2023]
Abstract
Background/objectives Sleeping behavior and individual prospensity in sleep timing during a 24 h period, known as chronotypes, are underestimated factors, which may favor the development of obesity and metabolic diseases. Furthermore, melatonin is known to play an important role in circadian rhythm, but was also suggested to directly influence metabolism and bodyweight regulation. Since disturbed and shifted sleep rhythms have been observed in adolescents with obesity, this study aimed to investigate potential interactions between melatonin secretion, chronobiology, and metabolism. In addition, the influence of artificial light especially emitted by electronic devices on these parameters was of further interest. Subjects/methods We performed a cross-sectional study including 149 adolescents (mean age 14.7 ± 2.1 years) with obesity. Metabolic blood parameters (e.g., cholesterol, triglycerides, uric acid, and insulin) were obtained from patients and correlated with nocturnal melatonin secretion. Melatonin secretion was determined by measuring 6-sulfatoxymelatonin (MT6s), the major metabolite of melatonin in the first-morning urine, and normalized to urinary creatinine levels to account for the urinary concentration. Chronobiologic parameters were further assessed using the Munich ChronoType Questionnaire. Results Subjects with insulin resistance (n = 101) showed significantly lower nocturnal melatonin levels compared to those with unimpaired insulin secretion (p = 0.006). Furthermore, triglyceride (p = 0.012) and elevated uric acid levels (p = 0.029) showed significant associations with melatonin secretion. Patients with late chronotype showed a higher incidence of insulin resistance (p = 0.018). Moreover, late chronotype and social jetlag were associated with the time and duration of media consumption. Conclusion We identified an association of impaired energy metabolism and lower nocturnal melatonin secretion in addition to late chronotype and increased social jetlag (misalignment of biological and social clocks) in adolescents with obesity. This might point towards a crucial role of chronotype and melatonin secretion as risk factors for the development of pediatric and adolescent obesity.
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Abstract
Melatonin is a hormonal product of the pineal gland, a fact that is often forgotten. Instead it is promoted as a dietary supplement that will overcome insomnia, as an antioxidant and as a prescription only drug in most countries outside the United States of America and Canada. The aim of this review is to step back and highlight what we know about melatonin following its discovery 60 years ago. What is the role of endogenous melatonin; what does melatonin do to sleep, body temperature, circadian rhythms, the cardiovascular system, reproductive system, endocrine system and metabolism when administered to healthy subjects? When used as a drug/dietary supplement, what safety studies have been conducted? Can we really say melatonin is safe when it has not been systematically studied and many studies show interactions with a wide range of physiological processes? Finally the results of studies investigating the efficacy of melatonin as a drug to alleviate insomnia are critically evaluated. In summary, melatonin is an endogenous pineal gland hormone with specific physiological functions in animals and humans, with its primary role in humans to maintain synchrony of sleep with the day/night cycle. When administered as a drug it affects a wide range of physiological systems and has clinically important drug interactions. With respect to efficacy for treating sleep disorders, melatonin can advance the time of sleep onset but the effect is modest and variable. In children with neurodevelopmental disabilities melatonin appears to have the greatest impact on sleep onset but little effect on sleep efficiency.
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Affiliation(s)
- David J Kennaway
- Robinson Research Institute and Adelaide School of Medicine, University of Adelaide, Adelaide, South Australia, Australia
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59
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Vejrazkova D, Vankova M, Vcelak J, Krejci H, Anderlova K, Tura A, Pacini G, Sumova A, Sladek M, Bendlova B. The rs10830963 Polymorphism of the MTNR1B Gene: Association With Abnormal Glucose, Insulin and C-peptide Kinetics. Front Endocrinol (Lausanne) 2022; 13:868364. [PMID: 35733780 PMCID: PMC9207528 DOI: 10.3389/fendo.2022.868364] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 04/25/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND The MTNR1B gene encodes a receptor for melatonin, a hormone regulating biorhythms. Disruptions in biorhythms contribute to the development of type 2 diabetes mellitus (T2DM). Genetic studies suggest that variability in the MTNR1B gene affects T2DM development. Our aim was to compare the distribution of the genetic variant rs10830963 between persons differing in glucose tolerance in a sample of the Czech population (N=1206). We also evaluated possible associations of the polymorphism with insulin sensitivity, beta cell function, with the shape of glucose, insulin and C-peptide trajectories measured 7 times during a 3-hour oral glucose tolerance test (OGTT) and with glucagon response. In a subgroup of 268 volunteers we also evaluated sleep patterns and biorhythm. RESULTS 13 persons were diagnosed with T2DM, 119 had impaired fasting blood glucose (IFG) and/or impaired glucose tolerance (IGT). 1074 participants showed normal results and formed a control group. A higher frequency of minor allele G was found in the IFG/IGT group in comparison with controls. The GG constellation was present in 23% of diabetics, in 17% of IFG/IGT probands and in 11% of controls. Compared to CC and CG genotypes, GG homozygotes showed higher stimulated glycemia levels during the OGTT. Homozygous as well as heterozygous carriers of the G allele showed lower very early phase of insulin and C-peptide secretion with unchanged insulin sensitivity. These differences remained significant after excluding diabetics and the IFG/IGT group from the analysis. No associations of the genotype with the shape of OGTT-based trajectories, with glucagon or with chronobiological patterns were observed. However, the shape of the trajectories differed significantly between men and women. CONCLUSION In a representative sample of the Czech population, the G allele of the rs10830963 polymorphism is associated with impaired early phase of beta cell function, and this is evident even in healthy individuals.
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Affiliation(s)
- Daniela Vejrazkova
- Department of Molecular Endocrinology, Institute of Endocrinology, Prague, Czechia
- *Correspondence: Daniela Vejrazkova,
| | - Marketa Vankova
- Department of Molecular Endocrinology, Institute of Endocrinology, Prague, Czechia
| | - Josef Vcelak
- Department of Molecular Endocrinology, Institute of Endocrinology, Prague, Czechia
| | - Hana Krejci
- Department of Obstetrics and Gynecology, 1st Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czechia
| | - Katerina Anderlova
- Department of Obstetrics and Gynecology, 1st Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czechia
| | - Andrea Tura
- Metabolic Unit, Institute of Neuroscience, National Research Council, Padova, Italy
| | - Giovanni Pacini
- Metabolic Unit, Institute of Neuroscience, National Research Council, Padova, Italy
| | - Alena Sumova
- Laboratory of Biological Rhythms, Institute of Physiology of the Czech Academy of Sciences, Prague, Czechia
| | - Martin Sladek
- Laboratory of Biological Rhythms, Institute of Physiology of the Czech Academy of Sciences, Prague, Czechia
| | - Bela Bendlova
- Department of Molecular Endocrinology, Institute of Endocrinology, Prague, Czechia
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Liu J, Li W, Liu B, Dai A, Wang Y, She L, Zhang P, Zheng W, Dai Q, Yang M. Melatonin Receptor 1B Genetic Variants on Susceptibility to Gestational Diabetes Mellitus: A Hospital-Based Case-Control Study in Wuhan, Central China. Diabetes Metab Syndr Obes 2022; 15:1207-1216. [PMID: 35480849 PMCID: PMC9035465 DOI: 10.2147/dmso.s345036] [Citation(s) in RCA: 3] [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: 10/27/2021] [Accepted: 04/01/2022] [Indexed: 11/23/2022] Open
Abstract
PURPOSE The aim of the study was to find out the associations of Melatonin receptor 1B (MTNR1B) genetic variants with gestational diabetes mellitus (GDM) in Wuhan of central China. PATIENTS AND METHODS A hospital-based case-control study that included 1679 women was carried out to explore the associations of MTNR1B single nucleotide polymorphisms (SNPs) with GDM risk, which were analyzed through logistic regression analysis by adjusting age, pre-pregnancy BMI and family history of diabetes. Multifactor dimensionality reduction was applied to determine gene-gene interactions between SNPs. RESULTS MTNR1B SNPs rs10830962, rs10830963, rs1387153, rs7936247 and rs4753426 were significantly associated with GDM risk (P<0.05). The rs10830962/G, rs10830963/G, rs1387153/T, and rs7936247/T were risk variants, whereas rs4753426/T was protective variant for GDM development. Fasting plasma glucose (FPG) and 1h-plasma glucose (PG) were significantly different among genotypes at rs10830962 and rs10830963, whereas 2h-PG levels were not. Gene-gene interactions were not found among the five SNPs on GDM risk. CONCLUSION MTNR1B genetic variants have significant associations but no gene-gene interactions with GDM risk in central Chinese population. Furthermore, MTNR1B SNPs have significant relationships with glycemic traits.
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Affiliation(s)
- Jianqiong Liu
- Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
| | - Wei Li
- Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
| | - Bei Liu
- Technical Guidance Institute, Jinan Family Planning Service Center, Jinan, Shandong Province, People's Republic of China
| | - Anna Dai
- School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
| | - Yanqin Wang
- Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
| | - Lu She
- School of Medicine, Wuhan University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
- Research Center for Health Promotion in Women, Youth and Children, Wuhan University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
| | - Pei Zhang
- School of Medicine, Wuhan University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
- Research Center for Health Promotion in Women, Youth and Children, Wuhan University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
| | - Wenpei Zheng
- Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
| | - Qiong Dai
- Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
| | - Mei Yang
- School of Medicine, Wuhan University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
- Research Center for Health Promotion in Women, Youth and Children, Wuhan University of Science and Technology, Wuhan, Hubei Province, People's Republic of China
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Nikolaev G, Robeva R, Konakchieva R. Membrane Melatonin Receptors Activated Cell Signaling in Physiology and Disease. Int J Mol Sci 2021; 23:ijms23010471. [PMID: 35008896 PMCID: PMC8745360 DOI: 10.3390/ijms23010471] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/28/2021] [Accepted: 12/29/2021] [Indexed: 02/07/2023] Open
Abstract
The pineal hormone melatonin has attracted great scientific interest since its discovery in 1958. Despite the enormous number of basic and clinical studies the exact role of melatonin in respect to human physiology remains elusive. In humans, two high-affinity receptors for melatonin, MT1 and MT2, belonging to the family of G protein-coupled receptors (GPCRs) have been cloned and identified. The two receptor types activate Gi proteins and MT2 couples additionally to Gq proteins to modulate intracellular events. The individual effects of MT1 and MT2 receptor activation in a variety of cells are complemented by their ability to form homo- and heterodimers, the functional relevance of which is yet to be confirmed. Recently, several melatonin receptor genetic polymorphisms were discovered and implicated in pathology-for instance in type 2 diabetes, autoimmune disease, and cancer. The circadian patterns of melatonin secretion, its pleiotropic effects depending on cell type and condition, and the already demonstrated cross-talks of melatonin receptors with other signal transduction pathways further contribute to the perplexity of research on the role of the pineal hormone in humans. In this review we try to summarize the current knowledge on the membrane melatonin receptor activated cell signaling in physiology and pathology and their relevance to certain disease conditions including cancer.
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Affiliation(s)
- Georgi Nikolaev
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
- Correspondence:
| | - Ralitsa Robeva
- Department of Endocrinology, Faculty of Medicine, Medical University, 1431 Sofia, Bulgaria;
| | - Rossitza Konakchieva
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
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The Association between Fasting Glucose and Sugar Sweetened Beverages Intake Is Greater in Latin Americans with a High Polygenic Risk Score for Type 2 Diabetes Mellitus. Nutrients 2021; 14:nu14010069. [PMID: 35010944 PMCID: PMC8746587 DOI: 10.3390/nu14010069] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/16/2021] [Accepted: 12/17/2021] [Indexed: 12/12/2022] Open
Abstract
Chile is one of the largest consumers of sugar-sweetened beverages (SSB) world-wide. However, it is unknown whether the effects from this highly industrialized food will mimic those reported in industrialized countries or whether they will be modified by local lifestyle or population genetics. Our goal is to evaluate the interaction effect between SSB intake and T2D susceptibility on fasting glucose. We calculated a weighted genetic risk score (GRSw) based on 16 T2D risk SNPs in 2828 non-diabetic participants of the MAUCO cohort. SSB intake was categorized in four levels using a food frequency questionnaire. Log-fasting glucose was regressed on SSB and GRSw tertiles while accounting for socio-demography, lifestyle, obesity, and Amerindian ancestry. Fasting glucose increased systematically per unit of GRSw (β = 0.02 ± 0.006, p = 0.00002) and by SSB intake (β[cat4] = 0.04 ± 0.01, p = 0.0001), showing a significant interaction, where the strongest effect was observed in the highest GRSw-tertile and in the highest SSB consumption category (β = 0.05 ± 0.02, p = 0.02). SNP-wise, SSB interacted with additive effects of rs7903146 (TCF7L2) (β = 0.05 ± 0.01, p = 0.002) and with the G/G genotype of rs10830963 (MTNRB1B) (β = 0.19 ± 0.05, p = 0.001). Conclusions: The association between SSB intake and fasting glucose in the Chilean population without diabetes is modified by T2D genetic susceptibility.
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Li-Gao R, Hughes DA, van Klinken JB, de Mutsert R, Rosendaal FR, Mook-Kanamori DO, Timpson NJ, Willems van Dijk K. Genetic Studies of Metabolomics Change After a Liquid Meal Illuminate Novel Pathways for Glucose and Lipid Metabolism. Diabetes 2021; 70:2932-2946. [PMID: 34610981 DOI: 10.2337/db21-0397] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 09/27/2021] [Indexed: 11/13/2022]
Abstract
Humans spend the greater part of the day in a postprandial state. However, the genetic basis of postprandial blood measures is relatively uncharted territory. We examined the genetics of variation in concentrations of postprandial metabolites (t = 150 min) in response to a liquid mixed meal through genome-wide association studies (GWAS) performed in the Netherlands Epidemiology of Obesity (NEO) study (n = 5,705). The metabolite response GWAS identified an association between glucose change and rs10830963:G in the melatonin receptor 1B (β [SE] -0.23 [0.03], P = 2.15 × 10-19). In addition, the ANKRD55 locus led by rs458741:C showed strong associations with extremely large VLDL (XXLVLDL) particle response (XXLVLDL total cholesterol: β [SE] 0.17 [0.03], P = 5.76 × 10-10; XXLVLDL cholesterol ester: β [SE] 0.17 [0.03], P = 9.74 × 10-10), which also revealed strong associations with body composition and diabetes in the UK Biobank (P < 5 × 10-8). Furthermore, the associations between XXLVLDL response and insulinogenic index, HOMA-β, Matsuda insulin sensitivity index, and HbA1c in the NEO study implied the role of chylomicron synthesis in diabetes (with false discovery rate-corrected q <0.05). To conclude, genetic studies of metabolomics change after a liquid meal illuminate novel pathways for glucose and lipid metabolism. Further studies are warranted to corroborate biological pathways of the ANKRD55 locus underlying diabetes.
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Affiliation(s)
- Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - David A Hughes
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, U.K
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
| | - Jan B van Klinken
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Nicholas J Timpson
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, U.K
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Division of Endocrinology, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
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Prasad RB, Kristensen K, Katsarou A, Shaat N. Association of single nucleotide polymorphisms with insulin secretion, insulin sensitivity, and diabetes in women with a history of gestational diabetes mellitus. BMC Med Genomics 2021; 14:274. [PMID: 34801028 PMCID: PMC8606068 DOI: 10.1186/s12920-021-01123-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 11/10/2021] [Indexed: 12/23/2022] Open
Abstract
Background This study investigated whether single nucleotide polymorphisms (SNPs) reported by previous genome-wide association studies (GWAS) to be associated with impaired insulin secretion, insulin resistance, and/or type 2 diabetes are associated with disposition index, the homeostasis model assessment of insulin resistance (HOMA-IR), and/or development of diabetes following a pregnancy complicated by gestational diabetes mellitus (GDM). Methods Seventy-two SNPs were genotyped in 374 women with previous GDM from Southern Sweden. An oral glucose tolerance test was performed 1–2 years postpartum, although data on the diagnosis of diabetes were accessible up to 5 years postpartum. HOMA-IR and disposition index were used to measure insulin resistance and secretion, respectively. Results The risk A-allele in the rs11708067 polymorphism of the adenylate cyclase 5 gene (ADCY5) was associated with decreased disposition index (beta = − 0.90, SE 0.38, p = 0.019). This polymorphism was an expression quantitative trait loci (eQTL) in islets for both ADCY5 and its antisense transcript. The risk C-allele in the rs2943641 polymorphism, near the insulin receptor substrate 1 gene (IRS1), showed a trend towards association with increased HOMA-IR (beta = 0.36, SE 0.18, p = 0.050), and the T-allele of the rs4607103 polymorphism, near the ADAM metallopeptidase with thrombospondin type 1 motif 9 gene (ADAMTS9), was associated with postpartum diabetes (OR = 2.12, SE 0.22, p = 0.00055). The genetic risk score (GRS) of the top four SNPs tested for association with the disposition index using equal weights was associated with the disposition index (beta = − 0.31, SE = 0.29, p = 0.00096). In addition, the GRS of the four SNPs studied for association with HOMA-IR using equal weights showed an association with HOMA-IR (beta = 1.13, SE = 0.48, p = 9.72874e−11). All analyses were adjusted for age, body mass index, and ethnicity. Conclusions This study demonstrated the genetic susceptibility of women with a history of GDM to impaired insulin secretion and sensitivity and, ultimately, to diabetes development.
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Affiliation(s)
- Rashmi B Prasad
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Karl Kristensen
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Obstetrics and Gynaecology, Skåne University Hospital, Malmö, Sweden
| | - Anastasia Katsarou
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Endocrinology, Skåne University Hospital, 205 02, Malmö, Sweden
| | - Nael Shaat
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden. .,Department of Endocrinology, Skåne University Hospital, 205 02, Malmö, Sweden.
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Lauritzen ES, Støy J, Bæch-Laursen C, Grarup N, Jessen N, Hansen T, Møller N, Hartmann B, Holst JJ, Kampmann U. The Effect of Melatonin on Incretin Hormones: Results From Experimental and Randomized Clinical Studies. J Clin Endocrinol Metab 2021; 106:e5109-e5123. [PMID: 34265066 DOI: 10.1210/clinem/dgab521] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Indexed: 01/10/2023]
Abstract
CONTEXT Glucose homeostasis is under circadian control through both endocrine and intracellular mechanisms, with several lines of evidence suggesting that melatonin affects glucose homeostasis. OBJECTIVE To evaluate the acute in vivo and in situ effects of melatonin on secretion of the incretin hormones, glucagon-like-peptide 1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP), and their impact on β-cell insulin secretion. DESIGN A human randomized, double-blinded, placebo-controlled crossover study combined with a confirmatory in situ study of perfused rat intestines. SETTING Aarhus University Hospital. METHODS Fifteen healthy male participants were examined 2 × 2 times: an oral glucose tolerance test (OGTT) was performed on day 1 and an isoglycemic IV glucose infusion replicating the blood glucose profile of the OGTT day was performed on day 2. These pairs of study days were repeated on treatment with melatonin and placebo, respectively. For the in situ study, 6 rat intestines and 4 rat pancreases were perfused arterially with perfusion buffer ± melatonin. The intestines were concomitantly perfused with glucose through the luminal compartment. RESULTS In humans, melatonin treatment resulted in reduced GIP secretion compared with placebo (ANOVA P = 0.003), an effect also observed in the perfused rat intestines (ANOVA P = 0.003), in which GLP-1 secretion also was impaired by arterial melatonin infusion (ANOVA P < 0.001). Despite a decrease in GIP levels, the in vivo glucose-stimulated insulin secretion was unaffected by melatonin (P = 0.78). CONCLUSION Melatonin reduced GIP secretion during an oral glucose challenge in healthy young men but did not affect insulin secretion. Reduced GIP secretion was confirmed in an in situ model of the rat intestine.
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Affiliation(s)
- Esben Stistrup Lauritzen
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Medical research laboratory, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Julie Støy
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Medical research laboratory, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Cecilie Bæch-Laursen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Jessen
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Research Laboratory for Biochemical Pathology, Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Møller
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Medical research laboratory, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Bolette Hartmann
- Novo Nordisk Foundation Center for Basic Metabolic Research, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens Juul Holst
- Novo Nordisk Foundation Center for Basic Metabolic Research, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulla Kampmann
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Medical research laboratory, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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Lauritzen ES, Kampmann U, Smedegaard SB, Støy J. Effects of daily administration of melatonin before bedtime on fasting insulin, glucose and insulin sensitivity in healthy adults and patients with metabolic diseases. A systematic review and meta-analysis. Clin Endocrinol (Oxf) 2021; 95:691-701. [PMID: 34370338 DOI: 10.1111/cen.14576] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 06/09/2021] [Accepted: 07/12/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND Melatonin is increasingly used as a pharmacological sleep aid but it is also emerging as a regulator of glucose homoeostasis. Yet, previous research has been ambiguous with reports of both positive and negative effects of melatonin on glucose metabolism. OBJECTIVES To assess the effect of daily treatment with melatonin on fasting glucose, insulin, insulin sensitivity and haemoglobin A1c (HbA1c) levels. DATA SOURCES MEDLINE, EMBASE, CENTRAL, clinicaltrials.gov and clinicaltrialsregister.eu were systematically searched. ELIGIBILITY CRITERIA, PARTICIPANTS AND INTERVENTIONS All randomized, placebo-controlled studies with melatonin treatment were assessed. We included studies with daily melatonin treatment (≥2 weeks) of healthy adults or patients with metabolic diseases. METHODS Hedges' g differences were calculated for the metabolic parameters of the included studies, heterogeneity was assessed with χ2 and I2 tests and meta-analyses were performed with the random-effects model. RESULTS Long-term treatment with melatonin did not change fasting glucose significantly compared with placebo (g: -0.07 [-0.22 to 0.08], n = 603) but it reduced fasting insulin levels slightly (g: -0.27 [-0.50 to -0.04], n = 278) and trended towards reduced insulin resistance (HOMA-IR) (g: -0.20 [-0.44 to 0.03], n = 278). HbA1c levels were largely unaffected by melatonin treatment compared with placebo (g: 0.14 [-0.19 to 0.46], n = 142). CONCLUSIONS With the available literature, melatonin seems to be a glucose-metabolic safe sleep aid in patients with metabolic diseases and in healthy adults. It may even have beneficial glucose-metabolic effects as fasting insulin levels were reduced in this meta-analysis, but the confidence intervals of the meta-analyses are wide, underscoring the need for further research within this field.
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Affiliation(s)
- Esben S Lauritzen
- The Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Medical/Steno Research Laboratory, Aarhus University, Aarhus, Denmark
| | - Ulla Kampmann
- The Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | - Stine B Smedegaard
- The Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | - Julie Støy
- The Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
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Abstract
Circadian disruption is pervasive and can occur at multiple organizational levels, contributing to poor health outcomes at individual and population levels. Evidence points to a bidirectional relationship, in that circadian disruption increases disease severity and many diseases can disrupt circadian rhythms. Importantly, circadian disruption can increase the risk for the expression and development of neurologic, psychiatric, cardiometabolic, and immune disorders. Thus, harnessing the rich findings from preclinical and translational research in circadian biology to enhance health via circadian-based approaches represents a unique opportunity for personalized/precision medicine and overall societal well-being. In this Review, we discuss the implications of circadian disruption for human health using a bench-to-bedside approach. Evidence from preclinical and translational science is applied to a clinical and population-based approach. Given the broad implications of circadian regulation for human health, this Review focuses its discussion on selected examples in neurologic, psychiatric, metabolic, cardiovascular, allergic, and immunologic disorders that highlight the interrelatedness between circadian disruption and human disease and the potential of circadian-based interventions, such as bright light therapy and exogenous melatonin, as well as chronotherapy to improve and/or modify disease outcomes.
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Affiliation(s)
- Anna B Fishbein
- Department of Pediatrics, Division of Pediatric Allergy and Immunology, Ann & Robert H. Lurie Children's Hospital, and
| | - Kristen L Knutson
- Department of Neurology and Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Phyllis C Zee
- Department of Neurology and Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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Li MD, Xin H, Yuan Y, Yang X, Li H, Tian D, Zhang H, Zhang Z, Han TL, Chen Q, Duan G, Ju D, Chen K, Deng F, He W. Circadian Clock-Controlled Checkpoints in the Pathogenesis of Complex Disease. Front Genet 2021; 12:721231. [PMID: 34557221 PMCID: PMC8452875 DOI: 10.3389/fgene.2021.721231] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 08/16/2021] [Indexed: 12/26/2022] Open
Abstract
The circadian clock coordinates physiology, metabolism, and behavior with the 24-h cycles of environmental light. Fundamental mechanisms of how the circadian clock regulates organ physiology and metabolism have been elucidated at a rapid speed in the past two decades. Here we review circadian networks in more than six organ systems associated with complex disease, which cluster around metabolic disorders, and seek to propose critical regulatory molecules controlled by the circadian clock (named clock-controlled checkpoints) in the pathogenesis of complex disease. These include clock-controlled checkpoints such as circadian nuclear receptors in liver and muscle tissues, chemokines and adhesion molecules in the vasculature. Although the progress is encouraging, many gaps in the mechanisms remain unaddressed. Future studies should focus on devising time-dependent strategies for drug delivery and engagement in well-characterized organs such as the liver, and elucidating fundamental circadian biology in so far less characterized organ systems, including the heart, blood, peripheral neurons, and reproductive systems.
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Affiliation(s)
- Min-Dian Li
- Department of Cardiology and the Center for Circadian Metabolism and Cardiovascular Disease, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Haoran Xin
- Department of Cardiology and the Center for Circadian Metabolism and Cardiovascular Disease, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Yinglin Yuan
- Medical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China
| | - Xinqing Yang
- Department of Anesthesiology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Hongli Li
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Dingyuan Tian
- Department of Cardiology and the Center for Circadian Metabolism and Cardiovascular Disease, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Hua Zhang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zhihui Zhang
- Department of Cardiology and the Center for Circadian Metabolism and Cardiovascular Disease, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Ting-Li Han
- Department of Obstetrics and Gynaecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Qing Chen
- Key Lab of Medical Protection for Electromagnetic Radiation, Ministry of Education of China, Institute of Toxicology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Guangyou Duan
- Department of Anesthesiology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Dapeng Ju
- Department of Anesthesiology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Ka Chen
- Research Center for Nutrition and Food Safety, Institute of Military Preventive Medicine, Army Medical University, Chongqing, China
| | - Fang Deng
- Key Laboratory of Extreme Environmental Medicine, Department of Pathophysiology, College of High Altitude Military Medicine, Ministry of Education of China, Army Medical University (Third Military Medical University), Chongqing, China.,Key Laboratory of High Altitude Medicine, PLA, Army Medical University (Third Military Medical University), Chongqing, China
| | - Wenyan He
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Buchanan VL, Wang Y, Blanco E, Graff M, Albala C, Burrows R, Santos JL, Angel B, Lozoff B, Voruganti VS, Guo X, Taylor KD, Chen YDI, Yao J, Tan J, Downie C, Highland HM, Justice AE, Gahagan S, North KE. Genome-wide association study identifying novel variant for fasting insulin and allelic heterogeneity in known glycemic loci in Chilean adolescents: The Santiago Longitudinal Study. Pediatr Obes 2021; 16:e12765. [PMID: 33381925 PMCID: PMC8711702 DOI: 10.1111/ijpo.12765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 11/25/2020] [Indexed: 12/01/2022]
Abstract
BACKGROUND The genetic underpinnings of glycemic traits have been understudied in adolescent and Hispanic/Latino (H/L) populations in comparison to adults and populations of European ancestry. OBJECTIVE To identify genetic factors underlying glycemic traits in an adolescent H/L population. METHODS We conducted a genome-wide association study (GWAS) of fasting glucose (FG) and fasting insulin (FI) in H/L adolescents from the Santiago Longitudinal Study. RESULTS We identified one novel variant positioned in the CSMD1 gene on chromosome 8 (rs77465890, effect allele frequency = 0.10) that was associated with FI (β = -0.299, SE = 0.054, p = 2.72×10-8 ) and was only slightly attenuated after adjusting for body mass index z-scores (β = -0.252, SE = 0.047, p = 1.03×10-7 ). We demonstrated directionally consistent, but not statistically significant results in African and Hispanic adults of the Population Architecture Using Genomics and Epidemiology Consortium. We also identified secondary signals for two FG loci after conditioning on known variants, which demonstrate allelic heterogeneity in well-known glucose loci. CONCLUSION Our results exemplify the importance of including populations with diverse ancestral origin and adolescent participants in GWAS of glycemic traits to uncover novel risk loci and expand our understanding of disease aetiology.
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Affiliation(s)
- Victoria L Buchanan
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yujie Wang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Estela Blanco
- Division of Academic General Pediatrics, Child Development and Community Health, University of California at San Diego, San Diego, California, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Cecilia Albala
- Department of Public Health Nutrition, Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - Raquel Burrows
- Department of Public Health Nutrition, Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - José L Santos
- Department of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Bárbara Angel
- Department of Public Health Nutrition, Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - Betsy Lozoff
- Department of Pediatrics, University of Michigan, Ann Arbor, Michigan, USA
| | - Venkata Saroja Voruganti
- Department of Nutrition and UNC Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Carolina Downie
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Anne E Justice
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania, USA
| | - Sheila Gahagan
- Division of Academic General Pediatrics, Child Development and Community Health, University of California at San Diego, San Diego, California, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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Chung RH, Chiu YF, Wang WC, Hwu CM, Hung YJ, Lee IT, Chuang LM, Quertermous T, Rotter JI, Chen YDI, Chang IS, Hsiung CA. Multi-omics analysis identifies CpGs near G6PC2 mediating the effects of genetic variants on fasting glucose. Diabetologia 2021; 64:1613-1625. [PMID: 33842983 DOI: 10.1007/s00125-021-05449-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 02/08/2021] [Indexed: 10/21/2022]
Abstract
AIMS/HYPOTHESIS An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses. METHODS We first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data. RESULTS Our meta-analysis identified 18 significant (p < 5 × 10-8) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the G6PC2 gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in G6PC2 as the instrument. CONCLUSIONS/INTERPRETATION Our analysis results suggest that rs2232326 and rs2232328 in G6PC2 may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in G6PC2 and CpGs near G6PC2 may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near G6PC2, an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose.
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Affiliation(s)
- Ren-Hua Chung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
| | - Yen-Feng Chiu
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Wen-Chang Wang
- The Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Yi-Jen Hung
- Division of Endocrine and Metabolism, Tri-Service General Hospital, Taipei, Taiwan
- Institute of Preventive Medicine, National Defense Medical Center, Taipei, Taiwan
| | - I-Te Lee
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Institutes of Molecular Medicine, Collage of Medicine, National Taiwan University, Taipei, Taiwan
| | - Thomas Quertermous
- Division of Cardiovascular Medicine and Stanford Cardiovascular Institute, Falk Cardiovascular Research Center, Stanford University, Stanford, CA, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, the Lundquist Institute, Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, the Lundquist Institute, Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - I-Shou Chang
- National Institute of Cancer Research, National Health Research Institutes, Zhunan, Taiwan
| | - Chao A Hsiung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
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71
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Griggs S, Strohl KP, Grey M, Barbato E, Margevicius S, Hickman RL. Circadian characteristics of the rest-activity rhythm, executive function, and glucose fluctuations in young adults with type 1 diabetes. Chronobiol Int 2021; 38:1477-1487. [PMID: 34128443 DOI: 10.1080/07420528.2021.1932987] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Circadian alignment is an important element in individual health, and one behavioral marker, rest-activity rhythm, could influence self-management in young adults with type 1 diabetes (T1D). Little is known about the rest-activity rhythms, executive function, and glycemia among young adults with type 1 diabetes (T1D). The purpose of this study was to evaluate parametric and nonparametric circadian characteristics of the rest-activity rhythm and the associations between these variables, sleep-wake behavior, executive function, and glycemia among young adults with T1D. Young adults with T1D, recruited from diabetes clinics, wore wrist actigraphs and a continuous glucose monitor (CGM) concurrently for 6-14 days. Participants completed a 3-minute Trail Making Test on paper and electronic questionnaires - 8-item PROMIS v1.0 Emotional Distress Scale, 17-item Diabetes Distress Scale, including twice-daily Pittsburgh sleep diaries. Cosinor and nonparametric analyses were used to compute the rest-activity rhythm parameters, and linear regression modeling procedures were performed to determine the associations among the study variables. The sample included 46 young adults (mean age 22.3 ± 3.2; 32.6% male; 84.8% non-Hispanic White, HbA1c mean 7.2 ± 1.1%, BMI mean 27.0 ± 4.4 kg/m2). A number of parametric associations were observed between a stronger rhythm, better objective sleep-wake characteristics, and less daytime sleepiness. Nonparametric circadian parameters were significantly associated with several outcomes: a stronger rhythm adherence (higher inter-daily stability) with better objective sleep-wake characteristics, better executive function, lower diabetes distress, less hyperglycemia risk, and more time spent in hypoglycemia/hypoglycemia risk; and a more robust rhythm (higher relative amplitude) with better objective sleep-wake characteristics and more time spent in hypoglycemia/higher hypoglycemia risk. Future work should be directed at designs that test causality, such as interventions directed at the strength and stability of rest-activity rhythms, for the potential to improve glucoregulation and other diabetes outcomes.
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Affiliation(s)
- Stephanie Griggs
- Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio, USA
| | - Kingman P Strohl
- Department of Physiology and Biophysics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Margaret Grey
- School of Nursing and School of Medicine, Yale University, West Haven, Connecticut, USA
| | - Eric Barbato
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Seunghee Margevicius
- Department of Population and Quantitative Health Sciences, School of Medicine, Cleveland, Ohio, USA
| | - Ronald L Hickman
- Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio, USA
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72
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Song JF, Zhang J, Zhang MZ, Ni J, Wang T, Zhao YQ, Khan NU. Evaluation of the effect of MTNR1B rs10830963 gene variant on the therapeutic efficacy of nateglinide in treating type 2 diabetes among Chinese Han patients. BMC Med Genomics 2021; 14:156. [PMID: 34118937 PMCID: PMC8196487 DOI: 10.1186/s12920-021-01004-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 06/01/2021] [Indexed: 12/02/2022] Open
Abstract
Genetic polymorphisms in the MTNR1B gene is associated with type 2 diabetes mellitus (T2DM); however, there is no evidence about its impact on the therapeutic efficacy of nateglinide. This prospective case-control study was designed to investigate the effect of MTNR1B rs10830963 gene variant on the therapeutic efficacy of nateglinide in treating T2DM. We genotyped untreated T2DM patients (N = 200) and healthy controls (N = 200) using the method of the high resolution of melting curve (HRM). Newly diagnosed T2DM patients (n = 60) with CYP2C9*1 and SLCO1B1 521TT genotypes were enrolled and given oral nateglinide (360 mg/d) for 8 weeks. The outcome was measured by collecting the venous blood samples before and at the 8th week of the treatment. The risk G allelic frequency of MTNR1B rs10830963 was higher in T2DM patients than the healthy subjects (P < 0.05). Post 8-week of treatment, newly diagnosed T2DM patients showed a less reduction in fasting plasma glucose levels and less increase in the carriers of genotype CG + GG at rs10830963 when compared with the CC genotype (P < 0.05). MTNR1B rs10830963 polymorphism was associated with the therapeutic efficacy of nateglinide in T2DM patients. Also, the CC homozygotes had a better effect than G allele carriers.Trial registration Chinese Clinical Trial Register ChiCTR13003536, date of registration: May 14, 2013.
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Affiliation(s)
- Jin-Fang Song
- Department of Pharmacy, Affiliated Hospital of Jiangnan University , No.1000, Hefeng Road, Wuxi, 214000, China
| | - Jie Zhang
- School of Pharmacy, Wannan Medical College, Wuhu, China
| | - Ming-Zhu Zhang
- Department of Pharmacy, Shandong Province Third Hospital, Jinan, 250000, China
| | - Jiang Ni
- Department of Pharmacy, Affiliated Hospital of Jiangnan University , No.1000, Hefeng Road, Wuxi, 214000, China
| | - Tao Wang
- Department of Endocrinology, Affiliated Hospital of Xuzhou Medical College, Xuzhou, 221000, China
| | - Yi-Qing Zhao
- Department of Pharmacy, Affiliated Hospital of Jiangnan University , No.1000, Hefeng Road, Wuxi, 214000, China.
| | - Naveed Ullah Khan
- Department of Pharmaceutics, College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China.
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73
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Arikoglu H, Erkoc-Kaya D, Ipekci SH, Gokturk F, Iscioglu F, Korez MK, Baldane S, Gonen MS. Type 2 diabetes is associated with the MTNR1B gene, a genetic bridge between circadian rhythm and glucose metabolism, in a Turkish population. Mol Biol Rep 2021; 48:4181-4189. [PMID: 34117605 DOI: 10.1007/s11033-021-06431-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 05/21/2021] [Indexed: 01/06/2023]
Abstract
Type 2 diabetes (T2D) is a complicated public health problem in Turkey as well as worldwide. Genome-wide approaches have been guiding in very challenging situations, such as the elucidation of genetic variations underlying complex diseases such as T2D. Despite intensive studies worldwide, few studies have determined the genetic susceptibility to T2D in Turkish populations. In this study, we investigated the effect of genes that are strongly associated with T2D in genome-wide association (GWA) studies, including MTNR1B, CDKAL1, THADA, ADAMTS9 and ENPP1, on T2D and its characteristic traits in a Turkish population. In 824 nonobese individuals (454 T2D patients and 370 healthy individuals), prominent variants of these GWA genes were genotyped by real-time PCR using the LightSNiP Genotyping Assay System. The SNP rs1387153 C/T, which is located 28 kb upstream of the MTNR1B gene, was significantly associated with T2D and fasting blood glucose levels (P < 0.05). The intronic SNP rs10830963 C/G in the MTNR1B gene was not associated with T2D, but it was associated with fasting blood glucose, HbA1C and LDL levels (P < 0.05). The other important GWA loci investigated in our study were not found to be associated with T2D or its traits. Only the SNP rs1044498 (A/C variation) in the ENPP1 gene was determined to be related to fasting blood glucose (P < 0.05). Our study suggests, consistent with the literature, that the MTNR1B locus, which has a prominent role in glucose regulation, is associated with T2D development by affecting blood glucose levels in our population.
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Affiliation(s)
- Hilal Arikoglu
- Department of Medical Biology, Faculty of Medicine, Selcuk University, Konya, Turkey.
| | - Dudu Erkoc-Kaya
- Department of Medical Biology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Suleyman Hilmi Ipekci
- Department of Endocrinology and Metabolic Diseases, Hisar Hospital Intercontinental, Istanbul, Turkey
| | - Fatma Gokturk
- Department of Medical Biology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Funda Iscioglu
- Department of Statistics, Faculty of Science, Ege University, Izmir, Turkey
| | - Muslu Kazim Korez
- Department of Biostatistics, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Suleyman Baldane
- Department of Endocrinology and Metabolic Diseases, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Mustafa Sait Gonen
- Department of Endocrinology and Metabolic Diseases, Faculty of Cerrahpasa Medicine, Istanbul University, Istanbul, Turkey
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74
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Gubin D, Neroev V, Malishevskaya T, Cornelissen G, Astakhov SY, Kolomeichuk S, Yuzhakova N, Kabitskaya Y, Weinert D. Melatonin mitigates disrupted circadian rhythms, lowers intraocular pressure, and improves retinal ganglion cells function in glaucoma. J Pineal Res 2021; 70:e12730. [PMID: 33730443 DOI: 10.1111/jpi.12730] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 03/11/2021] [Accepted: 03/12/2021] [Indexed: 02/06/2023]
Abstract
Glaucoma is a progressive optic neuropathy associated with damage to retinal ganglion cells (RGCs) and disrupted circadian rhythms. Melatonin is a promising substance to ameliorate glaucoma-associated compromised circadian rhythms, sleep, mood, and retinal cells function. However, studies estimating melatonin effects in glaucoma are currently lacking. Therefore, In this study, we investigated the effect of long-term (daily at 10:30 pm for 90 days) oral melatonin administration on systemic (Tb) and local to the organ of vision (IOP) circadian rhythms, pattern electroretinogram (PERG), sleep, and mood, depending on glaucoma stage in patients diagnosed with stable or advanced primary open-angle glaucoma. In a laboratory study in 15 of them, 24-hour records of salivary melatonin were obtained and MTNR1B receptor gene polymorphism was assessed. Melatonin increased the stability of the Tb circadian rhythm by improving its phase alignment and alignment with IOP. Melatonin time-dependently decreased IOP and IOP standard deviation (SD). IOP 24-hour mean and IOP SD decreases were more pronounced in individuals with the higher initial 24-hour IOP mean. Melatonin improved RGCs function in advanced glaucoma; N95 amplitude increase correlated positively with RGCs loss. The beneficial effects of melatonin on sleep and mood were greater in advanced glaucoma. Finally, delayed salivary melatonin and Tb phases were observed in MTNR1B G-allele carriers with advanced glaucoma. Combined, these results provide evidence for melatonin efficiency in restoring disrupted circadian rhythms in glaucoma with different effects of melatonin on systemic vs. local circadian rhythms, indicating that a personalized strategy of melatonin administration may further refine its treatment benefits.
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Affiliation(s)
- Denis Gubin
- Department of Biology, Medical University, Tyumen, Russia
- Tyumen Cardiology Research Center, Tomsk National Research Medical Center, Russian Academy of Science, Tomsk, Russia
| | - Vladimir Neroev
- Helmholtz Moscow Research Institute of Eye Diseases, Moscow, Russia
| | | | - Germaine Cornelissen
- Department of Integrated Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Sergei Y Astakhov
- Pavlov First Saint Petersburg State Medical University, St. Petersburg, Russia
| | - Sergey Kolomeichuk
- Laboratory of Genetics, Institute of Biology of the Karelian Science Center of the Russian Academy of Sciences, Petrozavodsk, Russia
| | | | - Yana Kabitskaya
- Center for Genomic Technologies, Northern Trans-Ural State Agricultural University, Tyumen, Russia
| | - Dietmar Weinert
- Institute of Biology/Zoology, Martin Luther University, Halle-Wittenberg, Germany
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75
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Pace NP, Vassallo J, Calleja-Agius J. Gestational diabetes, environmental temperature and climate factors - From epidemiological evidence to physiological mechanisms. Early Hum Dev 2021; 155:105219. [PMID: 33046275 DOI: 10.1016/j.earlhumdev.2020.105219] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Gestational diabetes (GDM) is a common metabolic complication of pregnancy that is generally asymptomatic in its clinical course, although it is potentially associated with a wide range of both maternal and foetal complications. The population prevalence of GDM varies widely, depending on the clinical diagnostic criteria, ethnicity, demographics and background prevalence of type 2 diabetes. Climate variability and environmental temperature have recently come to the forefront as potential direct or indirect determinants of human health. The association between GDM and environmental temperature is complex, and studies have often reported conflicting findings. Epidemiologic studies have shown a direct relation between rising environmental temperature and the risk of both GDM and impaired beta cell function. Seasonal trends in the prevalence of GDM have been reported in several populations, with a higher prevalence in summer months. Multiple mechanisms have been proposed to explain the GDM-temperature correlation. A growing body of evidence supports a link between temperature, energy expenditure and adipose tissue metabolism. Brown adipose tissue thermogenesis, induced by cold temperatures, improves insulin sensitivity. Further biological explanations for the GDM-temperature correlation lie in potential association with low vitamin D levels, which varies according to sunshine exposure. Observational studies are also complicated by lifestyle factors, such as diet and physical activity, that could exhibit seasonal variation. In this review article, we provide a systematic overview of available epidemiological evidence linking environmental temperature and gestational diabetes. Furthermore, the physiological mechanisms that give biological plausibility to association between GDM and temperature are explored. As future climate patterns could drive global changes in GDM prevalence, this knowledge has important implications for both clinicians and researchers.
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Affiliation(s)
- Nikolai Paul Pace
- Department of Anatomy, Faculty of Medicine and Surgery, Biomedical Sciences Building, University of Malta, Msida MSD 2080, Malta.
| | - Josanne Vassallo
- Department of Medicine, Faculty of Medicine and Surgery, Biomedical Sciences Building, University of Malta, Msida MSD 2080, Malta
| | - Jean Calleja-Agius
- Department of Anatomy, Faculty of Medicine and Surgery, Biomedical Sciences Building, University of Malta, Msida MSD 2080, Malta
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76
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Hughes AE, Hayes MG, Egan AM, Patel KA, Scholtens DM, Lowe LP, Lowe WL, Dunne FP, Hattersley AT, Freathy RM. All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes. Wellcome Open Res 2021; 5:175. [PMID: 33869792 PMCID: PMC8030121 DOI: 10.12688/wellcomeopenres.16097.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/09/2021] [Indexed: 11/20/2022] Open
Abstract
Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.
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Affiliation(s)
- Alice E Hughes
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | - M Geoffrey Hayes
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Aoife M Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic School of Medicine, Rochester, MN, USA
| | - Kashyap A Patel
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | | | - Lynn P Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - William L Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Fidelma P Dunne
- Galway Diabetes Research Centre and Saolta Hospital Group, National University of Ireland, Galway, Galway, Ireland
| | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
- National Institute for Health Research Exeter Clinical Research Facility, Exeter, UK
| | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
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77
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Analysis of Evolution and Ethnic Diversity at Glucose-Associated SNPs of Circadian Clock-Related Loci with Cryptochrome 1, Cryptochrome 2, and Melatonin receptor 1B. Biochem Genet 2021; 59:1173-1184. [PMID: 33709300 DOI: 10.1007/s10528-021-10045-y] [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: 11/16/2020] [Accepted: 01/29/2021] [Indexed: 10/21/2022]
Abstract
Diabetes shows high heritability and, worldwide, causes significant health problems including cardiovascular disease and stroke. There is significant variation in the frequency of diabetes between different populations. Both Cryptochromes and Melatonin have a major role to regulate the circadian clock. Circadian clock failure causes metabolic dysfunctions including diabetes and obesity. Variations in the Cryptochrome 1, the Cryptochrome 2, and the Melatonin receptor 1B (MTNR1B) genes show associations with fasting glucose, and are also related to circadian clock. Here, we analyzed evidence for genetic selection and ethnic diversity at circadian clock- and glucose-related gene loci associated with Cryptochrome 1, Cryptochrome 2, and MTNR1B. We carried out a 3-step genetic method to investigate genetic selection at the Cryptochrome 1, Cryptochrome 2, and MTNR1B on four populations from the 1000 Genomes Project and HapMap. First we used F-statistics to quantify genetic population differences and find ethnic diversity. Then we applied a long-range haplotype test to detect significant extreme long haplotypes, and then the integrated haplotype score (iHS) to find genetic selection at Cryptochrome 1, Cryptochrome 2, and MTNR1B. We observed genetic population differences and ethnic diversity at one glucose-associated Cryptochrome 1 single-nucleotide polymorphism (SNP) (rs8192440), one glucose-associated Cryptochrome 2 SNP (rs11605924), and one glucose-associated MTNR1B SNP (rs10830963) by F-statistics. Both Cryptochrome 1 and MTNR1B also showed selection by the iHS. These observations show new evidence for evolution at Cryptochrome 1, Cryptochrome 2 and MTNR1B. Further investigation should continue to examine the evolution of circadian clock- and glucose-related genes.
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78
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Kampmann U, Lauritzen ES, Grarup N, Jessen N, Hansen T, Møller N, Støy J. Acute metabolic effects of melatonin-A randomized crossover study in healthy young men. J Pineal Res 2021; 70:e12706. [PMID: 33220095 DOI: 10.1111/jpi.12706] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 11/11/2020] [Accepted: 11/15/2020] [Indexed: 01/12/2023]
Abstract
Melatonin regulates circadian rhythm, but may also have effects on glucose homeostasis. A common G-allele in the MTNR1B locus has been associated with an increased risk of type 2 diabetes (T2DM). We aimed to examine acute effects of high doses of melatonin on glucose metabolism with attention to MTNR1B genotype. Twenty men were examined in a double-blinded, randomized crossover study on two nonconsecutive days with four doses of 10 mg oral melatonin or placebo. Insulin sensitivity and insulin secretion were assessed by an intravenous glucose tolerance test (IVGTT) and a hyperinsulinaemic-euglycaemic clamp (HEC). Blood samples were drawn to determine the metabolic profile and MTNR1B rs10830963 genotype. Indirect calorimetry and blood pressure measurements were also performed. Insulin sensitivity index was significantly reduced on the melatonin day (P = .028) in the whole group and in homozygous carriers of the rs10830963 C-allele (P = .041). Glucose during the IVGTT was unaffected, but there was a tendency towards lower insulin and C-peptide levels in the first minutes after glucose administration in G-allele carriers. Systolic blood pressure decreased and lipid oxidation increased significantly on the melatonin day in rs10830963 G-allele carriers. Overall, our study reports that acute administration of melatonin in supra-physiological doses may have a negative impact on insulin sensitivity. Clinical trial registration number (clinicaltrial.gov): NCT03204877.
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Affiliation(s)
- Ulla Kampmann
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | - Esben S Lauritzen
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Medical Research Laboratory, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Niels Grarup
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Niels Jessen
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Research Laboratory for Biochemical Pathology, Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Torben Hansen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Niels Møller
- Medical Research Laboratory, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Julie Støy
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
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79
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Ruan W, Yuan X, Eltzschig HK. Circadian rhythm as a therapeutic target. Nat Rev Drug Discov 2021; 20:287-307. [PMID: 33589815 DOI: 10.1038/s41573-020-00109-w] [Citation(s) in RCA: 240] [Impact Index Per Article: 60.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/09/2020] [Indexed: 12/20/2022]
Abstract
The circadian clock evolved in diverse organisms to integrate external environmental changes and internal physiology. The clock endows the host with temporal precision and robust adaptation to the surrounding environment. When circadian rhythms are perturbed or misaligned, as a result of jet lag, shiftwork or other lifestyle factors, adverse health consequences arise, and the risks of diseases such as cancer, cardiovascular diseases or metabolic disorders increase. Although the negative impact of circadian rhythm disruption is now well established, it remains underappreciated how to take advantage of biological timing, or correct it, for health benefits. In this Review, we provide an updated account of the circadian system and highlight several key disease areas with altered circadian signalling. We discuss environmental and lifestyle modifications of circadian rhythm and clock-based therapeutic strategies, including chronotherapy, in which dosing time is deliberately optimized for maximum therapeutic index, and pharmacological agents that target core clock components and proximal regulators. Promising progress in research, disease models and clinical applications should encourage a concerted effort towards a new era of circadian medicine.
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Affiliation(s)
- Wei Ruan
- Department of Anesthesiology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.,Department of Anesthesiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Xiaoyi Yuan
- Department of Anesthesiology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Holger K Eltzschig
- Department of Anesthesiology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.
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80
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Dearden L, Bouret SG, Ozanne SE. Nutritional and developmental programming effects of insulin. J Neuroendocrinol 2021; 33:e12933. [PMID: 33438814 DOI: 10.1111/jne.12933] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 11/24/2020] [Accepted: 12/11/2020] [Indexed: 02/06/2023]
Abstract
The discovery of insulin in 1921 was a major breakthrough in medicine and for therapy in patients with diabetes. The dramatic rise in the prevalence of overweight and obesity has been tightly linked to an increased prevalence of gestational diabetes mellitus (GDM), which poses major health concerns. Babies born to GDM mothers are more likely to develop obesity, type 2 diabetes and cardiovascular disease later in life. Evidence accumulated during the past two decades has revealed that high levels insulin, such as those observed during GDM, can have a widespread effect on the development and function of a variety of organs. This review summarises our current knowledge on the role of insulin in the placenta, cardiovascular system and brain during critical periods of development, as well as how it can contribute to lifelong metabolic regulation. We also discuss possible intervention strategies to ameliorate and hopefully reverse the developmental defects associated with obesity and GDM.
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Affiliation(s)
- Laura Dearden
- MRC Metabolic Diseases Unit, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, University of Cambridge Metabolic Research Laboratories, Cambridge, UK
| | - Sebastien G Bouret
- Inserm, Laboratory of Development and Plasticity of the Neuroendocrine Brain, Lille Neuroscience & Cognition Research Center, Lille, France
- University of Lille, Lille, France
| | - Susan E Ozanne
- MRC Metabolic Diseases Unit, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, University of Cambridge Metabolic Research Laboratories, Cambridge, UK
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81
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Lagou V, Mägi R, Hottenga JJ, Grallert H, Perry JRB, Bouatia-Naji N, Marullo L, Rybin D, Jansen R, Min JL, Dimas AS, Ulrich A, Zudina L, Gådin JR, Jiang L, Faggian A, Bonnefond A, Fadista J, Stathopoulou MG, Isaacs A, Willems SM, Navarro P, Tanaka T, Jackson AU, Montasser ME, O'Connell JR, Bielak LF, Webster RJ, Saxena R, Stafford JM, Pourcain BS, Timpson NJ, Salo P, Shin SY, Amin N, Smith AV, Li G, Verweij N, Goel A, Ford I, Johnson PCD, Johnson T, Kapur K, Thorleifsson G, Strawbridge RJ, Rasmussen-Torvik LJ, Esko T, Mihailov E, Fall T, Fraser RM, Mahajan A, Kanoni S, Giedraitis V, Kleber ME, Silbernagel G, Meyer J, Müller-Nurasyid M, Ganna A, Sarin AP, Yengo L, Shungin D, Luan J, Horikoshi M, An P, Sanna S, Boettcher Y, Rayner NW, Nolte IM, Zemunik T, Iperen EV, Kovacs P, Hastie ND, Wild SH, McLachlan S, Campbell S, Polasek O, Carlson O, Egan J, Kiess W, Willemsen G, Kuusisto J, Laakso M, Dimitriou M, Hicks AA, Rauramaa R, Bandinelli S, Thorand B, Liu Y, Miljkovic I, Lind L, Doney A, Perola M, Hingorani A, Kivimaki M, Kumari M, Bennett AJ, Groves CJ, Herder C, Koistinen HA, Kinnunen L, et alLagou V, Mägi R, Hottenga JJ, Grallert H, Perry JRB, Bouatia-Naji N, Marullo L, Rybin D, Jansen R, Min JL, Dimas AS, Ulrich A, Zudina L, Gådin JR, Jiang L, Faggian A, Bonnefond A, Fadista J, Stathopoulou MG, Isaacs A, Willems SM, Navarro P, Tanaka T, Jackson AU, Montasser ME, O'Connell JR, Bielak LF, Webster RJ, Saxena R, Stafford JM, Pourcain BS, Timpson NJ, Salo P, Shin SY, Amin N, Smith AV, Li G, Verweij N, Goel A, Ford I, Johnson PCD, Johnson T, Kapur K, Thorleifsson G, Strawbridge RJ, Rasmussen-Torvik LJ, Esko T, Mihailov E, Fall T, Fraser RM, Mahajan A, Kanoni S, Giedraitis V, Kleber ME, Silbernagel G, Meyer J, Müller-Nurasyid M, Ganna A, Sarin AP, Yengo L, Shungin D, Luan J, Horikoshi M, An P, Sanna S, Boettcher Y, Rayner NW, Nolte IM, Zemunik T, Iperen EV, Kovacs P, Hastie ND, Wild SH, McLachlan S, Campbell S, Polasek O, Carlson O, Egan J, Kiess W, Willemsen G, Kuusisto J, Laakso M, Dimitriou M, Hicks AA, Rauramaa R, Bandinelli S, Thorand B, Liu Y, Miljkovic I, Lind L, Doney A, Perola M, Hingorani A, Kivimaki M, Kumari M, Bennett AJ, Groves CJ, Herder C, Koistinen HA, Kinnunen L, Faire UD, Bakker SJL, Uusitupa M, Palmer CNA, Jukema JW, Sattar N, Pouta A, Snieder H, Boerwinkle E, Pankow JS, Magnusson PK, Krus U, Scapoli C, de Geus EJCN, Blüher M, Wolffenbuttel BHR, Province MA, Abecasis GR, Meigs JB, Hovingh GK, Lindström J, Wilson JF, Wright AF, Dedoussis GV, Bornstein SR, Schwarz PEH, Tönjes A, Winkelmann BR, Boehm BO, März W, Metspalu A, Price JF, Deloukas P, Körner A, Lakka TA, Keinanen-Kiukaanniemi SM, Saaristo TE, Bergman RN, Tuomilehto J, Wareham NJ, Langenberg C, Männistö S, Franks PW, Hayward C, Vitart V, Kaprio J, Visvikis-Siest S, Balkau B, Altshuler D, Rudan I, Stumvoll M, Campbell H, van Duijn CM, Gieger C, Illig T, Ferrucci L, Pedersen NL, Pramstaller PP, Boehnke M, Frayling TM, Shuldiner AR, Peyser PA, Kardia SLR, Palmer LJ, Penninx BW, Meneton P, Harris TB, Navis G, Harst PVD, Smith GD, Forouhi NG, Loos RJF, Salomaa V, Soranzo N, Boomsma DI, Groop L, Tuomi T, Hofman A, Munroe PB, Gudnason V, Siscovick DS, Watkins H, Lecoeur C, Vollenweider P, Franco-Cereceda A, Eriksson P, Jarvelin MR, Stefansson K, Hamsten A, Nicholson G, Karpe F, Dermitzakis ET, Lindgren CM, McCarthy MI, Froguel P, Kaakinen MA, Lyssenko V, Watanabe RM, Ingelsson E, Florez JC, Dupuis J, Barroso I, Morris AP, Prokopenko I. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability. Nat Commun 2021; 12:24. [PMID: 33402679 PMCID: PMC7785747 DOI: 10.1038/s41467-020-19366-9] [Show More Authors] [Citation(s) in RCA: 96] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 09/22/2020] [Indexed: 12/20/2022] Open
Abstract
Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
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Affiliation(s)
- Vasiliki Lagou
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Department of Microbiology and Immunology, Laboratory of Adaptive Immunity, KU Leuven, Leuven, Belgium
- VIB-KU Leuven Center for Brain and Disease Research, Leuven, Belgium
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jouke- Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, VU University medical center, Amsterdam, the Netherlands
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD, München-Neuherberg, Germany
| | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Nabila Bouatia-Naji
- University of Lille Nord de France, Lille, France
- CNRS UMR8199, Institut Pasteur de Lille, Lille, France
- INSERM U970, Paris Cardiovascular Research Center PARCC, 75006, Paris, France
| | - Letizia Marullo
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Denis Rybin
- Boston University Data Coordinating Center, Boston, MA, USA
| | - Rick Jansen
- Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands
| | - Josine L Min
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Antigone S Dimas
- Institute for Bioinnovation, Biomedical Sciences Research Center Al. Fleming, Vari, Greece
| | - Anna Ulrich
- Department of Medicine, Imperial College London, London, UK
| | | | - Jesper R Gådin
- Cardiovascular Medicine Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Karolinska University Hospital, Solna, Sweden
| | - Longda Jiang
- Department of Medicine, Imperial College London, London, UK
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | | | - Amélie Bonnefond
- University of Lille Nord de France, Lille, France
- CNRS UMR8199, Institut Pasteur de Lille, Lille, France
- Department of Medicine, Imperial College London, London, UK
| | - Joao Fadista
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | | | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- CARIM School for Cardiovascular Diseases and Maastricht Centre for Systems Biology (MaCSBio, Maastricht University, Maastricht, the Netherlands
- Department of Physiology, Maastricht University, Maastricht, the Netherlands
| | - Sara M Willems
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Pau Navarro
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Toshiko Tanaka
- Translational Gerontology Branch, Longitudinal Study Section, National Institute on Aging, Baltimore, MD, USA
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland, School of Medicine, Baltimore, MD, USA
| | - Jeff R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland, School of Medicine, Baltimore, MD, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Rebecca J Webster
- Laboratory for Cancer Medicine, Harry Perkins Institute of Medical Research, University of Western Australia Centre for Medical Research, Nedlands, WA, Australia
| | - Richa Saxena
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Departmentartment of Anesthesia, Critical Care and Pain Medicine, MGH, Boston, MA, USA
| | - Jeanette M Stafford
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Beate St Pourcain
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Perttu Salo
- Public Health Genomics Unit, Department of Chronic Disease Prevention, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - So-Youn Shin
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Najaf Amin
- Department of Epidemiology Erasmus MC, Rotterdam, the Netherlands
| | - Albert V Smith
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Guo Li
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anuj Goel
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Paul C D Johnson
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
- Institute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Glasgow, UK
| | - Toby Johnson
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Karen Kapur
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | | | - Rona J Strawbridge
- Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska University Hospital Solna, Stockholm, Sweden
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Evelin Mihailov
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tove Fall
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Ross M Fraser
- Usher Institute, University of Edinburgh, Edinburgh, UK
- Synpromics Ltd, Roslin Innovation Centre, Easter Bush Campus, Edinburgh, EH25 9RG, UK
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Genentech, 340 Point San Bruno Boulevard, South San Francisco, CA, 94080, USA
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Wellcome Trust Sanger Institute, Hinxton, UK
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala Universitet, Uppsala, Sweden
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Günther Silbernagel
- Division of Angiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Julia Meyer
- Institute of Genetic Epidemiology,Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology,Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology and Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-University, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI, University Medical Center, Johannes Gutenberg University, 55101, Mainz, Germany
| | - Andrea Ganna
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Loic Yengo
- University of Lille Nord de France, Lille, France
- CNRS UMR8199, Institut Pasteur de Lille, Lille, France
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Dmitry Shungin
- Department of Public Health & Clinical Medicine, Umeå University, Umeå, Sweden
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, Malmö, Sweden
- Department of Odontology, Umeå University, Umeå, Sweden
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Momoko Horikoshi
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- RIKEN, Center for Integrative Medical Sciences, Laboratory for Endocrinology, Metabolism and Kidney Disease, Yokohama, Japan
| | - Ping An
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Serena Sanna
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, Italy
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Yvonne Boettcher
- Department of Medicine, University of Leipzig, Leipzig, Germany
- IFB AdiposityDiseases, University of Leipzig, Leipzig, Germany
| | - N William Rayner
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Sanger Institute, Hinxton, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Erik van Iperen
- Department of Clinical Epidemiology and Biostatistics, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Peter Kovacs
- IFB AdiposityDiseases, University of Leipzig, Leipzig, Germany
| | - Nicholas D Hastie
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Sarah H Wild
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | | | - Susan Campbell
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Ozren Polasek
- Faculty of Medicine, University of Split, Split, Croatia
| | - Olga Carlson
- Laboratory of Clinical Investigation, National Institute of Aging, Baltimore, MD, USA
| | - Josephine Egan
- Laboratory of Clinical Investigation, National Institute of Aging, Baltimore, MD, USA
| | - Wieland Kiess
- IFB AdiposityDiseases, University of Leipzig, Leipzig, Germany
- Pediatric Research Center, Department of Women's & Child Health, University of Leipzig, Leipzig, Germany
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Maria Dimitriou
- Department of Dietetics-Nutrition, Harokopio University, Athens, Greece
| | - Andrew A Hicks
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC) (Affiliated Institute of the University of LübeckLübeckGermany), Bolzano, Italy
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | | | - Barbara Thorand
- German Center for Diabetes Research (DZD, München-Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Iva Miljkovic
- Department of Epidemiology, Center for Aging and Population Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Akademiska sjukhuset, Uppsala, Sweden
| | - Alex Doney
- Pat McPherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Molecular and Clinical Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Markus Perola
- Public Health Genomics Unit, Department of Chronic Disease Prevention, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Aroon Hingorani
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Meena Kumari
- Department of Epidemiology and Public Health, University College London, London, UK
- University of Essex, Wivenhoe Park, Colchester, Essex, UK
| | - Amanda J Bennett
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Christopher J Groves
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Christian Herder
- German Center for Diabetes Research (DZD, München-Neuherberg, Germany
- Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Heikki A Koistinen
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
- Department of Medicine, University of Helsinki and Helsinki University Central Hospital, P.O. Box 340, Haartmaninkatu 4, Helsinki, FI-00029, Finland
- Minerva Foundation Institute for Medical Research, Biomedicum 2U, Tukholmankatu 8, Helsinki, FI-00290, Finland
| | - Leena Kinnunen
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
| | - Ulf de Faire
- Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Stephan J L Bakker
- Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Matti Uusitupa
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Colin N A Palmer
- Pat McPherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Molecular and Clinical Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - J Wouter Jukema
- Dept of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Anneli Pouta
- Department of Government Services, Finnish Institute for Health and Welfare, Helsinki, Finland
- PEDEGO Research Unit, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Eric Boerwinkle
- IMM Center for Human Genetics, University of Texas Health Science Center at Houston, Houston, TX, USA
- Division of Epidemiology, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MiI, USA
| | - Patrik K Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ulrika Krus
- Department of Clinical Sciences, Diabetes and Endocrinology Research Unit, University Hospital Malmö, Lund University, Malmö, Sweden
| | - Chiara Scapoli
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Eco J C N de Geus
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, VU University medical center, Amsterdam, the Netherlands
| | - Matthias Blüher
- Department of Medicine, University of Leipzig, Leipzig, Germany
- Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Bruce H R Wolffenbuttel
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Michael A Province
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Goncalo R Abecasis
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - James B Meigs
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- General Medicine Division, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - G Kees Hovingh
- Department of Vascular Medicine, Amsterdam UMC, Amsterdam, the Netherlands
- Novo Nordisk A/S, Copenhagen, Denmark
| | - Jaana Lindström
- Finnish Institute for Health and Welfare, Diabetes Prevention Unit, Helsinki, Finland
| | - James F Wilson
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Alan F Wright
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | | | - Stefan R Bornstein
- Department of Medicine, Division for Prevention and Care of Diabetes, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Peter E H Schwarz
- Department for Prevention and Care of Diabetes, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Paul Langerhans Institute Dresden of the Helmholtz Center Munich at University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
- IFB AdiposityDiseases, University of Leipzig, Leipzig, Germany
| | | | - Bernhard O Boehm
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore and Imperial College London, Singapore, Singapore
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, Germany
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Wellcome Trust Sanger Institute, Hinxton, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Antje Körner
- IFB AdiposityDiseases, University of Leipzig, Leipzig, Germany
- Diabetes Research Center, Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Timo A Lakka
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine/Physiology, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
| | - Sirkka M Keinanen-Kiukaanniemi
- Faculty of Medicine, Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Unit of General Practice, Oulu University Hospital, Oulu, Finland
| | - Timo E Saaristo
- Finnish Diabetes Association, Tampere, Finland
- Pirkanmaa Hospital District, Tampere, Finland
| | - Richard N Bergman
- Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jaakko Tuomilehto
- Department of Chronic Disease Prevention, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Satu Männistö
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, P.O. Box 30, Helsinki, FI-00271, Finland
| | - Paul W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, Malmö, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA
- Department of Public Health & Clinical Medicine, Units of Medicine and Nutritional Research, Umeå University, Umeå, Sweden
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Veronique Vitart
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | | | - Beverley Balkau
- Inserm, CESP Center for Research in Epidemiology and Public Health, U1018, Villejuif, France
- Univ Paris-Saclay, Univ Paris Sud, UVSQ, UMRS 1018, UMRS 1018, Villejuif, France
| | - David Altshuler
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Igor Rudan
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Michael Stumvoll
- Department of Medicine, University of Leipzig, Leipzig, Germany
- IFB AdiposityDiseases, University of Leipzig, Leipzig, Germany
| | | | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Centre for Medical Systems Biology, Leiden, the Netherlands
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD, München-Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
- Institute of Human Genetics, Hannover Medical School, Hannover, Germany
| | - Luigi Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Peter P Pramstaller
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC) (Affiliated Institute of the University of LübeckLübeckGermany), Bolzano, Italy
- Department of Neurology, General Central Hospital, Bolzano, Italy
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Timothy M Frayling
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, UK
| | - Alan R Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland, School of Medicine, Baltimore, MD, USA
- The Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Lyle J Palmer
- School of Public Health, University of Adelaide, Adelaide, Australia
| | - Brenda W Penninx
- Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands
| | - Pierre Meneton
- U872 Institut National de la Santé et de la Recherche Médicale, Centre de Recherche des Cordeliers, 75006, Paris, France
| | - Tamara B Harris
- Geriatric Epidemiology Section, Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, MD, USA
| | - Gerjan Navis
- Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
| | - Nita G Forouhi
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Ruth J F Loos
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Veikko Salomaa
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Nicole Soranzo
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Leif Groop
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland
- Department of Clinical Sciences, Diabetes and Endocrinology Research Unit, University Hospital Malmö, Lund University, Malmö, Sweden
| | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland
- Department of Clinical Sciences, Diabetes and Endocrinology Research Unit, University Hospital Malmö, Lund University, Malmö, Sweden
- Endocrinology, Abdominal Centre, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, University of Helsinki and Folkhälsan Research Center, Helsinki, Finland
| | - Albert Hofman
- Department of Epidemiology Erasmus MC, Rotterdam, the Netherlands
- Netherlands Consortium for healthy ageing, the Hague, the Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine University of Iceland, Reykjavik, Iceland
| | - David S Siscovick
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Hugh Watkins
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Cecile Lecoeur
- University of Lille Nord de France, Lille, France
- CNRS UMR8199, Institut Pasteur de Lille, Lille, France
| | - Peter Vollenweider
- Department of Medicine, University Hospital Lausanne, Lausanne, Switzerland
| | - Anders Franco-Cereceda
- Cardiothoracic Surgery Unit, Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Per Eriksson
- Cardiovascular Medicine Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Karolinska University Hospital, Solna, Sweden
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics and HPA-MRC Center, School of Public Health, Imperial College London, London, UK
- Institue of Health Sciences, University of Oulu, Oulu, Finland
| | - Kari Stefansson
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Anders Hamsten
- Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska University Hospital Solna, Stockholm, Sweden
- Department of Cardiology, Karolinska University Hospital Solna, Stockholm, Sweden
| | | | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Emmanouil T Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Cecilia M Lindgren
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford, UK
- Genentech, 340 Point San Bruno Boulevard, South San Francisco, CA, 94080, USA
| | - Philippe Froguel
- University of Lille Nord de France, Lille, France
- CNRS UMR8199, Institut Pasteur de Lille, Lille, France
- Department of Medicine, Imperial College London, London, UK
| | - Marika A Kaakinen
- Department of Medicine, Imperial College London, London, UK
- School of Biosciences and Medicine, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology Research Unit, University Hospital Malmö, Lund University, Malmö, Sweden
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Richard M Watanabe
- Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA
- Department of Physiology & Neuroscience, Keck School of Medicine of USC, Los Angeles, CA, USA
- USC Diabetes and Obesity Research Institute, Los Angeles, CA, USA
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, 94305, USA
| | - Jose C Florez
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Research Center, Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Inês Barroso
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, UK
- Exeter Centre of ExcEllence in Diabetes (ExCEED), University of Exeter Medical School, Exeter, UK
| | - Andrew P Morris
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Department of Biostatistics, University of Liverpool, Liverpool, UK
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Inga Prokopenko
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
- Department of Medicine, Imperial College London, London, UK.
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK.
- School of Biosciences and Medicine, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK.
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre Russian Academy of Sciences, Ufa, Russian Federation.
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Ramirez AVG, Filho DR, de Sá LBPC. Melatonin and its Relationships with Diabetes and Obesity: A Literature Review. Curr Diabetes Rev 2021; 17:e072620184137. [PMID: 32718296 DOI: 10.2174/1573399816666200727102357] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 07/13/2020] [Accepted: 07/15/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Obesity is an important clinical entity, causing many public health issues. Around two billion people in the world are overweight and obese. Almost 40% of American adults are obese and Brazil has about 18 million obese people. Nowadays, 415 million people have diabetes, around 1 in every 11 adults. These numbers will rise to 650 million people within 20 years. Melatonin shows a positive profile on the regulation of the metabolism of the human body. OBJECTIVE This study aimed to carry out a broad narrative review of the metabolic profile and associations between melatonin, diabetes and obesity. METHODS Article reviews, systematic reviews, prospective studies, retrospective studies, randomized, double-blind, and placebo-controlled trials in humans recently published were selected and analyzed. A total of 368 articles were collated and submitted to the eligibility analysis. Subsequently, 215 studies were selected to compose the content part of the paper, and 153 studies composed the narrative review. RESULTS Studies suggest a possible role of melatonin in metabolic diseases such as obesity, T2DM and metabolic syndrome. Intervention studies using this hormone in metabolic diseases are still unclear regarding the possible benefit of it. There is so far no consensus about the possible role of melatonin as an adjuvant in the treatment of metabolic diseases. More studies are necessary to define possible risks and benefits of melatonin as a therapeutic agent.
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Affiliation(s)
- Ana V G Ramirez
- Clinic Ana Valeria (CAV)- Clinic of Nutrition and Health Science, Street Antônio José Martins Filho, 300, Sao Jose do Rio Preto SP, 15092-230, Brazil
| | - Durval R Filho
- Associacao Brasileira de Nutrologia (ABRAN)/Brazilian Association of Nutrology, Catanduva/SP, Rua Belo Horizonte, 909 - Centro, Catanduva SP, Brazil
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83
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Sayed S, Nabi AHMN. Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1307:457-498. [PMID: 32314317 DOI: 10.1007/5584_2020_518] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.
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Affiliation(s)
- Shomoita Sayed
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh
| | - A H M Nurun Nabi
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh.
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84
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Yahaya TO, Salisu T, Abdulrahman YB, Umar AK. Update on the genetic and epigenetic etiology of gestational diabetes mellitus: a review. EGYPTIAN JOURNAL OF MEDICAL HUMAN GENETICS 2020; 21:13. [DOI: 10.1186/s43042-020-00054-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 02/11/2020] [Indexed: 02/08/2023] Open
Abstract
Abstract
Background
Many studies have been conducted on the genetic and epigenetic etiology of gestational diabetes mellitus (GDM) in the last two decades because of the disease’s increasing prevalence and role in global diabetes mellitus (DM) explosion. An update on the genetic and epigenetic etiology of GDM then becomes imperative to better understand and stem the rising incidence of the disease. This review, therefore, articulated GDM candidate genes and their pathophysiology for the awareness of stakeholders.
Main body (genetic and epigenetic etiology, GDM)
The search discovered 83 GDM candidate genes, of which TCF7L2, MTNR1B, CDKAL1, IRS1, and KCNQ1 are the most prevalent. Certain polymorphisms of these genes can modulate beta-cell dysfunction, adiposity, obesity, and insulin resistance through several mechanisms. Environmental triggers such as diets, pollutants, and microbes may also cause epigenetic changes in these genes, resulting in a loss of insulin-boosting and glucose metabolism functions. Early detection and adequate management may resolve the condition after delivery; otherwise, it will progress to maternal type 2 diabetes mellitus (T2DM) and fetal configuration to future obesity and DM. This shows that GDM is a strong risk factor for T2DM and, in rare cases, type 1 diabetes mellitus (T1DM) and maturity-onset diabetes of the young (MODY). This further shows that GDM significantly contributes to the rising incidence and burden of DM worldwide and its prevention may reverse the trend.
Conclusion
Mutations and epigenetic changes in certain genes are strong risk factors for GDM. For affected individuals with such etiologies, medical practitioners should formulate drugs and treatment procedures that target these genes and their pathophysiology.
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Abstract
PURPOSE OF REVIEW In this review, we summarize studies investigating genetics of gestational diabetes mellitus (GDM) and glucose metabolism in pregnancy. We describe these studies in the context of the larger body of literature on type 2 diabetes (T2D) and glycemic trait genomics. RECENT FINDINGS We reviewed 23 genetic association studies for GDM and performed a meta-analysis, which revealed variants at eight T2D loci significantly associated with GDM after the Bonferroni correction. These studies suggest that GDM and T2D share a number of genetic risk loci. Only two unbiased genome-wide association studies (GWASs) have successfully revealed genetic associations for GDM and related glycemic traits in pregnancy. A GWAS for GDM in Korean women identified two loci (near CDKAL1 and MTNR1B) known to be associated with T2D, though the association of the MTNR1B locus with GDM appears to be stronger than that for T2D. A multi-ethnic GWAS for glycemic traits in pregnancy identified two novel loci (near HKDC1 and BACE2) which appear to be associated with post-load glucose and fasting c-peptide specifically in pregnant women. There are ongoing efforts to use this genetic information, in the form of polygenic scores, to predict risk of GDM and postpartum T2D. The body of literature examining genetic associations with GDM is limited, especially when compared to the available literature on T2D and glycemic trait genomics. Additional genetic discovery for glucose metabolism in pregnant women will require larger pregnancy cohorts and international collaborative efforts. Studies on the clinical implications of these findings are also warranted.
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Affiliation(s)
- Camille E Powe
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Soo Heon Kwak
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
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Hughes AE, Hayes MG, Egan AM, Patel KA, Scholtens DM, Lowe LP, Lowe WL, Dunne FP, Hattersley AT, Freathy RM. All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes. Wellcome Open Res 2020; 5:175. [PMID: 33869792 PMCID: PMC8030121.2 DOI: 10.12688/wellcomeopenres.16097.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/13/2020] [Indexed: 04/02/2024] Open
Abstract
Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.
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Affiliation(s)
- Alice E Hughes
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | - M Geoffrey Hayes
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Aoife M Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic School of Medicine, Rochester, MN, USA
| | - Kashyap A Patel
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | | | - Lynn P Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - William L Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Fidelma P Dunne
- Galway Diabetes Research Centre and Saolta Hospital Group, National University of Ireland, Galway, Galway, Ireland
| | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
- National Institute for Health Research Exeter Clinical Research Facility, Exeter, UK
| | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
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Sorlí JV, Barragán R, Coltell O, Portolés O, Pascual EC, Ortega-Azorín C, González JI, Estruch R, Saiz C, Pérez-Fidalgo A, Ordovas JM, Corella D. Chronological Age Interacts with the Circadian Melatonin Receptor 1B Gene Variation, Determining Fasting Glucose Concentrations in Mediterranean Populations. Additional Analyses on Type-2 Diabetes Risk. Nutrients 2020; 12:nu12113323. [PMID: 33138317 PMCID: PMC7692445 DOI: 10.3390/nu12113323] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 10/21/2020] [Accepted: 10/24/2020] [Indexed: 12/25/2022] Open
Abstract
Gene-age interactions have not been systematically investigated on metabolic phenotypes and this modulation will be key for a better understanding of the temporal regulation in nutrigenomics. Taking into account that aging is typically associated with both impairment of the circadian system and a decrease in melatonin secretion, we focused on the melatonin receptor 1B (MTNR1B)-rs10830963 C>G variant that has been associated with fasting glucose concentrations, gestational diabetes, and type-2 diabetes. Therefore, our main aim was to investigate whether the association between the MTNR1B-rs10830963 polymorphism and fasting glucose is age dependent. Our secondary aims were to analyze the polymorphism association with type-2 diabetes and explore the gene-pregnancies interactions on the later type-2 diabetes risk. Three Mediterranean cohorts (n = 2823) were analyzed. First, a cross-sectional study in the discovery cohort consisting of 1378 participants (aged 18 to 80 years; mean age 41 years) from the general population was carried out. To validate and extend the results, two replication cohorts consisting of elderly individuals were studied. In the discovery cohort, we observed a strong gene-age interaction (p = 0.001), determining fasting glucose in such a way that the increasing effect of the risk G-allele was much greater in young (p = 5.9 × 10-10) than in elderly participants (p = 0.805). Consistently, the association of the MTNR1B-rs10830963 polymorphism with fasting glucose concentrations in the two replication cohorts (mean age over 65 years) did not reach statistical significance (p > 0.05 for both). However, in the elderly cohorts, significant associations between the polymorphism and type-2 diabetes at baseline were found. Moreover, in one of the cohorts, we obtained a statistically significant interaction between the MTNR1B polymorphism and the number of pregnancies, retrospectively assessed, on the type-2 diabetes risk. In conclusion, the association of the MTNR1B-rs10830963 polymorphism with fasting glucose is age-dependent, having a greater effect in younger people. However, in elderly subjects, associations of the polymorphism with type-2 diabetes were observed and our exploratory analysis suggested a modulatory effect of the number of past pregnancies on the future type-2 diabetes genetic risk.
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Affiliation(s)
- Jose V. Sorlí
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - Rocío Barragán
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
- Department of Medicine, Sleep Center of Excellence, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Oscar Coltell
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
- Department of Computer Languages and Systems, Universitat Jaume I, 12071 Castellón, Spain
| | - Olga Portolés
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - Eva C. Pascual
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
| | - Carolina Ortega-Azorín
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - José I. González
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - Ramon Estruch
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
- Department of Internal Medicine, Hospital Clinic, Institut d’Investigació Biomèdica August Pi i Sunyer (IDIBAPS), University of Barcelona, Villarroel, 170, 08036 Barcelona, Spain
| | - Carmen Saiz
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - Alejandro Pérez-Fidalgo
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Cáncer, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Jose M. Ordovas
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111, USA;
- Precision Nutrition and Obesity Program, IMDEA Alimentación, 28049 Madrid, Spain
| | - Dolores Corella
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
- Correspondence: ; Tel.: +34-96-386-4800
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Li Y, Lv Y, Bian C, You X, Shi Q. Molecular evolution of melatonin receptor genes (mtnr) in vertebrates and its shedding light on mtnr1c. Gene 2020; 769:145256. [PMID: 33164759 DOI: 10.1016/j.gene.2020.145256] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 10/05/2020] [Accepted: 10/20/2020] [Indexed: 12/15/2022]
Abstract
Melatonin receptors (MTNRs) play important roles in regulation of circadian rhythms and seasonal reproduction. However, their origin and evolution in vertebrates have not been investigated. Here, we performed a comprehensive examination by comparative genome mining of MTNRs in vertebrates. We successfully extracted 164 putative encoding sequences for MTNRs (including 57 mtnr1a, 59 mtnr1b and 48 mtnr1c) from 45 high-quality representative genomes. Interestingly, the putative expansions of mtnr1a and mtnr1b in zebrafish were also identified in other Cyprinifomes, but not in other orders of teleost. Using phylogenetic interference, we observed this expansion to be clustered into a primitive position of the Actinopterygii, which may be resulted from teleost-specific genome duplication. The C-terminal extension of MTNR1C, predicted to be proteoglycan 4 (PRG4), originated after the speciation of Monotremata or Marsupialia. Our present genomics survey provides novel insights into the evolution of MTNRs in vertebrates and updates our understanding of these proteins.
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Affiliation(s)
- Yanping Li
- Key Laboratory of Sichuan Province for Fishes Conservation and Utilization in the Upper Reaches of the Yangtze River, College of Life Sciences, Neijiang Normal University, Neijiang 641100, China; Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen 518083, China
| | - Yunyun Lv
- Key Laboratory of Sichuan Province for Fishes Conservation and Utilization in the Upper Reaches of the Yangtze River, College of Life Sciences, Neijiang Normal University, Neijiang 641100, China
| | - Chao Bian
- Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen 518083, China
| | - Xinxin You
- Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen 518083, China
| | - Qiong Shi
- Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen 518083, China.
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Imam A, Winnebeck EC, Buchholz N, Froguel P, Bonnefond A, Solimena M, Ivanova A, Bouvier M, Plouffe B, Charpentier G, Karamitri A, Jockers R, Roenneberg T, Vetter C. Circadian, Sleep and Caloric Intake Phenotyping in Type 2 Diabetes Patients With Rare Melatonin Receptor 2 Mutations and Controls: A Pilot Study. Front Physiol 2020; 11:564140. [PMID: 33162895 PMCID: PMC7583701 DOI: 10.3389/fphys.2020.564140] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 09/07/2020] [Indexed: 01/27/2023] Open
Abstract
Background Melatonin modulates circadian rhythms in physiology and sleep initiation. Genetic variants of the MTNR1B locus, encoding the melatonin MT2 receptor, have been associated with increased type 2 diabetes (T2D) risk. Carriers of the common intronic MTNR1B rs10830963 T2D risk variant have modified sleep and circadian traits such as changes of the melatonin profile. However, it is currently unknown whether rare variants in the MT2 coding region are also associated with altered sleep and circadian phenotypes, including meal timing. Materials and Methods In this pilot study, 28 individuals [50% male; 46–82 years old; 50% with rare MT2 mutations (T2D MT2)] wore actigraphy devices and filled out daily food logs for 4 weeks. We computed circadian, sleep, and caloric intake phenotypes, including sleep duration, timing, and regularity [assessed by the Sleep Regularity Index (SRI)]; composite phase deviations (CPD) as well a sleep timing-based proxy for circadian misalignment; and caloric intake patterns throughout the day. Using regression analyses, we estimated age- and sex-adjusted mean differences (MD) and 95% confidence intervals (95%CI) between the two patient groups. Secondary analyses also compare T2D MT2 to 15 healthy controls. Results Patients with rare MT2 mutations had a later sleep onset (MD = 1.23, 95%CI = 0.42;2.04), and midsleep time (MD = 0.91, 95%CI = 0.12;1.70), slept more irregularly (MD in SRI = −8.98, 95%CI = −16.36;−1.60), had higher levels of behavioral circadian misalignment (MD in CPD = 1.21, 95%CI = 0.51;1.92), were more variable in regard to duration between first caloric intake and average sleep offset (MD = 1.08, 95%CI = 0.07;2.08), and had more caloric episodes in a 24 h day (MD = 1.08, 95%CI = 0.26;1.90), in comparison to T2D controls. Secondary analyses showed similar patterns between T2D MT2 and non-diabetic controls. Conclusion This pilot study suggests that compared to diabetic controls, T2D MT2 patients display a number of adverse sleep, circadian, and caloric intake phenotypes, including more irregular behavioral timing. A prospective study is needed to determine the role of these behavioral phenotypes in T2D onset and severity, especially in view of rare MT2 mutations.
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Affiliation(s)
- Akram Imam
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, United States
| | - Eva C Winnebeck
- Institute of Medical Psychology, Ludwig Maximilian University, Munich, Germany
| | - Nina Buchholz
- Institute of Medical Psychology, Ludwig Maximilian University, Munich, Germany
| | - Philippe Froguel
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille University Hospital, Lille, France.,Department of Metabolism, Imperial College London, London, United Kingdom
| | - Amélie Bonnefond
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille University Hospital, Lille, France.,Department of Metabolism, Imperial College London, London, United Kingdom
| | - Michele Solimena
- Paul Langerhans Institute Dresden of the Helmholtz Center Munich at the Technische Universität Dresden, Dresden, Germany
| | - Anna Ivanova
- Paul Langerhans Institute Dresden of the Helmholtz Center Munich at the Technische Universität Dresden, Dresden, Germany
| | - Michel Bouvier
- Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada
| | - Bianca Plouffe
- Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada.,School of Medicine, Dentistry and Biomedical Sciences, Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, United Kingdom
| | - Guillaume Charpentier
- Centre d'Études et de Recherches pour l'Intensification du Traitement du Diabète (CERITD), Sud-Francilien Hospital, Corbeil-Essonnes, France
| | | | - Ralf Jockers
- Université de Paris, Institut Cochin, INSERM, CNRS, Paris, France
| | - Till Roenneberg
- Institute of Medical Psychology, Ludwig Maximilian University, Munich, Germany
| | - Céline Vetter
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, United States.,Institute of Medical Psychology, Ludwig Maximilian University, Munich, Germany
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90
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Kim YH, Lazar MA. Transcriptional Control of Circadian Rhythms and Metabolism: A Matter of Time and Space. Endocr Rev 2020; 41:5835826. [PMID: 32392281 PMCID: PMC7334005 DOI: 10.1210/endrev/bnaa014] [Citation(s) in RCA: 82] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 05/04/2020] [Indexed: 02/07/2023]
Abstract
All biological processes, living organisms, and ecosystems have evolved with the Sun that confers a 24-hour periodicity to life on Earth. Circadian rhythms arose from evolutionary needs to maximize daily organismal fitness by enabling organisms to mount anticipatory and adaptive responses to recurrent light-dark cycles and associated environmental changes. The clock is a conserved feature in nearly all forms of life, ranging from prokaryotes to virtually every cell of multicellular eukaryotes. The mammalian clock comprises transcription factors interlocked in negative feedback loops, which generate circadian expression of genes that coordinate rhythmic physiology. In this review, we highlight previous and recent studies that have advanced our understanding of the transcriptional architecture of the mammalian clock, with a specific focus on epigenetic mechanisms, transcriptomics, and 3-dimensional chromatin architecture. In addition, we discuss reciprocal ways in which the clock and metabolism regulate each other to generate metabolic rhythms. We also highlight implications of circadian biology in human health, ranging from genetic and environment disruptions of the clock to novel therapeutic opportunities for circadian medicine. Finally, we explore remaining fundamental questions and future challenges to advancing the field forward.
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Affiliation(s)
- Yong Hoon Kim
- Institute for Diabetes, Obesity, and Metabolism, and Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Mitchell A Lazar
- Institute for Diabetes, Obesity, and Metabolism, and Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
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91
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Saki N, Sarhangi N, Afshari M, Bandarian F, Aghaei Meybodi HR, Hasanzad M. MTNR1B common genetic variant is associated with type 2 diabetes mellitus risk. GENE REPORTS 2020. [DOI: 10.1016/j.genrep.2020.100695] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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92
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Tanaka K, Okada Y, Maiko H, Mori H, Tanaka Y. Associations between urinary 6-sulfatoxymelatonin excretion and diabetic vascular complications or arteriosclerosis in patients with type 2 diabetes. J Diabetes Investig 2020; 12:601-609. [PMID: 33460308 PMCID: PMC8015816 DOI: 10.1111/jdi.13374] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 07/14/2020] [Accepted: 07/16/2020] [Indexed: 11/29/2022] Open
Abstract
AIMS/INTRODUCTION There are limited reports on the association between melatonin levels and vascular complications in patients with type 2 diabetes. The aim of this study was to determine the association between urinary 6-sulfatoxymelatonin, which is a urinary metabolite of melatonin, and diabetic vascular complications or arteriosclerosis in patients with type 2 diabetes. MATERIALS AND METHODS This retrospective study included patients (167 patients with type 2 diabetes and 27 patients without diabetes adjusted for age and sex) admitted to the hospital who underwent measurement of urinary 6-sulfatoxymelatonin. The urinary 6-sulfatoxymelatonin/creatinine ratio (6-SMT) was calculated. RESULTS The natural logarithmically scaled 6-SMT level (Ln 6-SMT) was significantly lower in type 2 diabetes patients (1.9 ± 1.1) compared with patients without diabetes (2.8 ± 1.0, P < 0.001). Multivariate linear regression analysis identified duration of diabetes, smoking status, urinary albumin-to-creatinine ratio, retinopathy and coronary heart disease as factors that could influence Ln 6-SMT levels in type 2 diabetes patients (R2 = 0.232, P < 0.001). Ln 6-SMT was associated with decreased odds of diabetic retinopathy, even after adjustment for various confounding factors (odds ratio 0.559, 95% confidence interval 0.369-0.846, P = 0.006). Similarly, Ln 6-SMT was associated with decreased odds of coronary heart disease (odds ratio 0.442, P = 0.030). CONCLUSIONS Our results showed the presence of low levels of Ln 6-SMT in type 2 diabetes patients relative to patients without diabetes. Furthermore, Ln 6-SMT is an independent risk factor of diabetic retinopathy and coronary heart diseases. These findings suggest that 6-SMT could be a useful biomarker for the prediction of micro- and macrovasculopathies in patients with type 2 diabetes.
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Affiliation(s)
- Kenichi Tanaka
- First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Yosuke Okada
- First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Hajime Maiko
- First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Hiroko Mori
- First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Yoshiya Tanaka
- First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan
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93
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Hughes AE, Hayes MG, Egan AM, Patel KA, Scholtens DM, Lowe LP, Lowe Jr WL, Dunne FP, Hattersley AT, Freathy RM. All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes. Wellcome Open Res 2020; 5:175. [PMID: 33869792 PMCID: PMC8030121 DOI: 10.12688/wellcomeopenres.16097.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/09/2020] [Indexed: 04/02/2024] Open
Abstract
Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.
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Affiliation(s)
- Alice E. Hughes
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | - M. Geoffrey Hayes
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Aoife M. Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic School of Medicine, Rochester, MN, USA
| | - Kashyap A. Patel
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | | | - Lynn P. Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - Fidelma P. Dunne
- Galway Diabetes Research Centre and Saolta Hospital Group, National University of Ireland, Galway, Galway, Ireland
| | - Andrew T. Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
- National Institute for Health Research Exeter Clinical Research Facility, Exeter, UK
| | - Rachel M. Freathy
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
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94
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Dou J, Wu D, Ding L, Wang K, Jiang M, Chai X, Reilly DF, Tai ES, Liu J, Sim X, Cheng S, Wang C. Using off-target data from whole-exome sequencing to improve genotyping accuracy, association analysis and polygenic risk prediction. Brief Bioinform 2020; 22:5857014. [PMID: 32591784 DOI: 10.1093/bib/bbaa084] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 04/09/2020] [Accepted: 04/21/2020] [Indexed: 12/12/2022] Open
Abstract
Whole-exome sequencing (WES) has been widely used to study the role of protein-coding variants in genetic diseases. Non-coding regions, typically covered by sparse off-target data, are often discarded by conventional WES analyses. Here, we develop a genotype calling pipeline named WEScall to analyse both target and off-target data. We leverage linkage disequilibrium shared within study samples and from an external reference panel to improve genotyping accuracy. In an application to WES of 2527 Chinese and Malays, WEScall can reduce the genotype discordance rate from 0.26% (SE= 6.4 × 10-6) to 0.08% (SE = 3.6 × 10-6) across 1.1 million single nucleotide polymorphisms (SNPs) in the deeply sequenced target regions. Furthermore, we obtain genotypes at 0.70% (SE = 3.0 × 10-6) discordance rate across 5.2 million off-target SNPs, which had ~1.2× mean sequencing depth. Using this dataset, we perform genome-wide association studies of 10 metabolic traits. Despite of our small sample size, we identify 10 loci at genome-wide significance (P < 5 × 10-8), including eight well-established loci. The two novel loci, both associated with glycated haemoglobin levels, are GPATCH8-SLC4A1 (rs369762319, P = 2.56 × 10-12) and ROR2 (rs1201042, P = 3.24 × 10-8). Finally, using summary statistics from UK Biobank and Biobank Japan, we show that polygenic risk prediction can be significantly improved for six out of nine traits by incorporating off-target data (P < 0.01). These results demonstrate WEScall as a useful tool to facilitate WES studies with decent amounts of off-target data.
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Affiliation(s)
- Jinzhuang Dou
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Degang Wu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lin Ding
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kai Wang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Minghui Jiang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | | | | | - E Shyong Tai
- Saw Swee Hock School of Public Health, Duke-NUS Medical School, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jianjun Liu
- Genome Institute of Singapore and a professor at Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Shanshan Cheng
- Ministry of Education Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chaolong Wang
- Ministry of Education Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Avitabile M, Succoio M, Testori A, Cardinale A, Vaksman Z, Lasorsa VA, Cantalupo S, Esposito M, Cimmino F, Montella A, Formicola D, Koster J, Andreotti V, Ghiorzo P, Romano MF, Staibano S, Scalvenzi M, Ayala F, Hakonarson H, Corrias MV, Devoto M, Law MH, Iles MM, Brown K, Diskin S, Zambrano N, Iolascon A, Capasso M. Neural crest-derived tumor neuroblastoma and melanoma share 1p13.2 as susceptibility locus that shows a long-range interaction with the SLC16A1 gene. Carcinogenesis 2020; 41:284-295. [PMID: 31605138 PMCID: PMC7346310 DOI: 10.1093/carcin/bgz153] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2019] [Revised: 08/28/2019] [Accepted: 09/04/2019] [Indexed: 12/27/2022] Open
Abstract
Neuroblastoma (NB) and malignant cutaneous melanoma (CMM) are neural crest cells (NCC)-derived tumors and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association studies (GWAS). We took a three-staged approach to conduct cross-disease meta-analysis of GWAS for NB and CMM (2101 NB cases and 4202 controls; 12 874 CMM cases and 23 203 controls) to identify shared loci. Findings were replicated in 1403 NB cases and 1403 controls of European ancestry and in 636 NB, 508 CMM cases and 2066 controls of Italian origin. We found a cross-association at locus 1p13.2 (rs2153977, odds ratio = 0.91, P = 5.36 × 10-8). We also detected a suggestive (P < 10-7) NB-CMM cross-association at 2q37.1 with opposite effect on cancer risk. Pathway analysis of 110 NB-CMM risk loci with P < 10-4 demonstrated enrichment of biological processes such as cell migration, cell cycle, metabolism and immune response, which are essential of human NCC development, underlying both tumors. In vitro and in silico analyses indicated that the rs2153977-T protective allele, located in an NB and CMM enhancer, decreased expression of SLC16A1 via long-range loop formation and altered a T-box protein binding site. Upon depletion of SLC16A1, we observed a decrease of cellular proliferation and invasion in both NB and CMM cell lines, suggesting its role as oncogene. This is the largest study to date examining pleiotropy across two NC cell-derived tumors identifying 1p13.2 as common susceptibility locus for NB and CMM risk. We demonstrate that combining genome-wide association studies results across cancers with same origins can identify new loci common to neuroblastoma and melanoma arising from tissues which originate from neural crest cells. Our results also show 1p13.2 confer risk to neuroblastoma and melanoma by regulating SLC16A1.
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Affiliation(s)
- Marianna Avitabile
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy
- CEINGE Biotecnologie Avanzate, Naples, Italy
| | | | - Alessandro Testori
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Antonella Cardinale
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy
- CEINGE Biotecnologie Avanzate, Naples, Italy
| | - Zalman Vaksman
- Division of Oncology and Center for Childhood Cancer Research, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Vito Alessandro Lasorsa
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy
- CEINGE Biotecnologie Avanzate, Naples, Italy
| | | | - Matteo Esposito
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy
| | | | | | | | - Jan Koster
- Department of Oncogenomics, Academic Medical Center, University of Amsterdam, Meibergdreef, Amsterdam, The Netherlands
| | - Virginia Andreotti
- Dipartimento di Medicina Oncologica Integrata, Università degli Studi di Genova,Genova, Italy
| | - Paola Ghiorzo
- Dipartimento di Medicina Oncologica Integrata, Università degli Studi di Genova,Genova, Italy
| | - Maria Fiammetta Romano
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Stefania Staibano
- Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Massimiliano Scalvenzi
- Dipartimento di Medicina clinica e Chirurgia, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Fabrizio Ayala
- National Cancer Institute, ‘Fondazione G. Pascale’-IRCCS, Naples, Italy
| | - Hakon Hakonarson
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Marcella Devoto
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Translational and Precision Medicine, University of Rome Sapienza, Rome, Italy
| | - Matthew H Law
- Statistical Genetics, QIMR Berghofer Medical Research Institute Brisbane, Queensland, Australia
| | - Mark M Iles
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Kevin Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sharon Diskin
- Division of Oncology and Center for Childhood Cancer Research, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicola Zambrano
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy
- CEINGE Biotecnologie Avanzate, Naples, Italy
| | - Achille Iolascon
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy
- CEINGE Biotecnologie Avanzate, Naples, Italy
| | - Mario Capasso
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy
- CEINGE Biotecnologie Avanzate, Naples, Italy
- IRCCS SDN, Naples, Italy
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Firneisz G, Rosta K, Rigó J, Nádasdi Á, Harreiter J, Kautzky-Willer A, Somogyi A. Identification and Potential Clinical Utility of the MTNR1B rs10830963 Core Gene Variant Associated to Endophenotypes in Gestational Diabetes Mellitus. Front Genet 2020; 11:332. [PMID: 32373162 PMCID: PMC7186410 DOI: 10.3389/fgene.2020.00332] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 03/20/2020] [Indexed: 01/28/2023] Open
Affiliation(s)
- Gábor Firneisz
- 2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary
- MTA-SE Molecular Medicine Research Group, Hungarian Academy of Sciences - Semmelweis University, Budapest, Hungary
| | - Klara Rosta
- Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria
- 1st Department of Obstetrics and Gynecology, Semmelweis University, Budapest, Hungary
| | - János Rigó
- 1st Department of Obstetrics and Gynecology, Semmelweis University, Budapest, Hungary
| | - Ákos Nádasdi
- 2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary
| | - Jürgen Harreiter
- Gender Medicine Unit, Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Alexandra Kautzky-Willer
- Gender Medicine Unit, Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Anikó Somogyi
- 2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary
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de Luis DA, Izaola O, Primo D, Aller R. A circadian rhythm-related MTNR1B genetic variant (rs10830963) modulate body weight change and insulin resistance after 9 months of a high protein/low carbohydrate vs a standard hypocaloric diet. J Diabetes Complications 2020; 34:107534. [PMID: 32057567 DOI: 10.1016/j.jdiacomp.2020.107534] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 01/06/2020] [Accepted: 01/08/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND & AIMS The risk allele (G) of rs10830963 in the melatonin receptor 1 B (MTNR1B) gene presents an association with biochemical parameters and obesity. We study the effect of this SNP on insulin resistance and weight loss secondary to two hypocaloric diets. METHODS 270 obese subjects were randomly allocated during 9 months (Diet HP: a high protein/low carbohydrate vs. Diet S: a standard severe hypocaloric diets). Anthropometric parameters, fasting blood glucose, C-reactive protein (CRP), insulin concentration, insulin resistance (HOMA-IR), lipid profile and adipocytokines levels were measured. Genotype of MTNR1B gene polymorphism (rs10830963) was evaluated. RESULTS All adiposity parameters, systolic blood pressure and leptin levels decreased in all subjects after both diets. This improvement of adiposity parameters was higher in non-G allele carriers than G allele carriers. After weight loss with Diet HP, (CC vs. CG + GG at 9 months); total cholesterol (delta: -9.9 ± 2.4 mg/dl vs. -4.8 ± 2.2 mg/dl:p < 0.05), LDL-cholesterol (delta: -8.3 ± 1.9 mg/dl vs. -5.1 ± 2.2 mg/dl: p < 0.05), insulin (delta: -4.7 ± 0.8 UI/L vs. -0.9 ± 1.0 UI/L: p < 0.05), triglycerides (delta: -17.7 ± 3.9 mg/dl vs. -6.1 ± 2.8 mg/dl: p < 0.05) and HOMA IR (delta: -0.8 ± 0.2 units vs. -0.2 ± 0.1 units: p < 0.05) improved only in no G allele carriers. After weight loss with Diet S in non G allele carriers, insulin levels (delta (CC vs. CG + GG): -3.4 ± 0.6 UI/L vs. -1.2 ± 0.4 UI/L: p < 0.05), triglycerides (delta: -29.2 ± 3.4 mg/dl vs. -8.2 ± 3.8 mg/dl: p < 0.05), HOMA-IR (delta (CC vs. CG + GG): -1.1 ± 0.2 units vs. -0.1 ± 0.1 units: p < 0.05), total cholesterol (delta: -15.9 ± 7.4 mg/dl vs. -5.8 ± 2.9 mg/dl:ns) and LDL-cholesterol (delta: -13.7 ± 5.9 mg/dl vs. -6.0 ± 2.9 mg/dl: ns) decreased, too. CONCLUSIONS our study detected a relationship of rs10830963 variant of MTNR1B gene with adiposity changes, cholesterol changes and insulin resistance modification induced by two different hypocaloric during 9 months.
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Affiliation(s)
- Daniel Antonio de Luis
- Endocrinology and Nutrition Research Center, School of Medicine, Department of Endocrinology and Nutrition, Hospital Clinico Universitario, University of Valladolid, Valladolid, Spain.
| | - Olatz Izaola
- Endocrinology and Nutrition Research Center, School of Medicine, Department of Endocrinology and Nutrition, Hospital Clinico Universitario, University of Valladolid, Valladolid, Spain
| | - David Primo
- Endocrinology and Nutrition Research Center, School of Medicine, Department of Endocrinology and Nutrition, Hospital Clinico Universitario, University of Valladolid, Valladolid, Spain
| | - Rocio Aller
- Endocrinology and Nutrition Research Center, School of Medicine, Department of Endocrinology and Nutrition, Hospital Clinico Universitario, University of Valladolid, Valladolid, Spain
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Krentz NAJ, Gloyn AL. Insights into pancreatic islet cell dysfunction from type 2 diabetes mellitus genetics. Nat Rev Endocrinol 2020; 16:202-212. [PMID: 32099086 DOI: 10.1038/s41574-020-0325-0] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/17/2020] [Indexed: 12/30/2022]
Abstract
Type 2 diabetes mellitus (T2DM) is an increasingly prevalent multifactorial disease that has both genetic and environmental risk factors, resulting in impaired glucose homeostasis. Genome-wide association studies (GWAS) have identified over 400 genetic signals that are associated with altered risk of T2DM. Human physiology and epigenomic data support a central role for the pancreatic islet in the pathogenesis of T2DM. This Review focuses on the promises and challenges of moving from genetic associations to molecular mechanisms and highlights efforts to identify the causal variant and effector transcripts at T2DM GWAS susceptibility loci. In addition, we examine current human models that are used to study both β-cell development and function, including EndoC-β cell lines and human induced pluripotent stem cell-derived β-like cells. We use examples of four T2DM susceptibility loci (CDKAL1, MTNR1B, SLC30A8 and PAM) to emphasize how a holistic approach involving genetics, physiology, and cellular and developmental biology can disentangle disease mechanisms at T2DM GWAS signals.
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Affiliation(s)
- Nicole A J Krentz
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
| | - Anna L Gloyn
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford, UK.
- Stanford Diabetes Research Centre, Stanford University, Stanford, CA, USA.
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99
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Mason IC, Qian J, Adler GK, Scheer FAJL. Impact of circadian disruption on glucose metabolism: implications for type 2 diabetes. Diabetologia 2020; 63:462-472. [PMID: 31915891 PMCID: PMC7002226 DOI: 10.1007/s00125-019-05059-6] [Citation(s) in RCA: 205] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 08/19/2019] [Indexed: 12/21/2022]
Abstract
The circadian system generates endogenous rhythms of approximately 24 h, the synchronisation of which are vital for healthy bodily function. The timing of many physiological processes, including glucose metabolism, are coordinated by the circadian system, and circadian disruptions that desynchronise or misalign these rhythms can result in adverse health outcomes. In this review, we cover the role of the circadian system and its disruption in glucose metabolism in healthy individuals and individuals with type 2 diabetes mellitus. We begin by defining circadian rhythms and circadian disruption and then we provide an overview of circadian regulation of glucose metabolism. We next discuss the impact of circadian disruptions on glucose control and type 2 diabetes. Given the concurrent high prevalence of type 2 diabetes and circadian disruption, understanding the mechanisms underlying the impact of circadian disruption on glucose metabolism may aid in improving glycaemic control.
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Affiliation(s)
- Ivy C Mason
- Brigham and Women's Hospital, Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, 221 Longwood Avenue, Boston, MA, 02115, USA
- Division of Sleep Medicine, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jingyi Qian
- Brigham and Women's Hospital, Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, 221 Longwood Avenue, Boston, MA, 02115, USA
- Division of Sleep Medicine, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gail K Adler
- Division of Endocrinology, Diabetes and Hypertension, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Frank A J L Scheer
- Brigham and Women's Hospital, Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, 221 Longwood Avenue, Boston, MA, 02115, USA.
- Division of Sleep Medicine, Department of Medicine, Harvard Medical School, Boston, MA, USA.
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Garaulet M, Qian J, Florez JC, Arendt J, Saxena R, Scheer FAJL. Melatonin Effects on Glucose Metabolism: Time To Unlock the Controversy. Trends Endocrinol Metab 2020; 31:192-204. [PMID: 31901302 PMCID: PMC7349733 DOI: 10.1016/j.tem.2019.11.011] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 11/19/2019] [Accepted: 11/21/2019] [Indexed: 12/18/2022]
Abstract
The past decade has witnessed a revival of interest in the hormone melatonin, partly attributable to the discovery that genetic variation in MTNR1B - the melatonin receptor gene - is a risk factor for impaired fasting glucose and type 2 diabetes (T2D). Despite intensive investigation, there is considerable confusion and seemingly conflicting data on the metabolic effects of melatonin and MTNR1B variation, and disagreement on whether melatonin is metabolically beneficial or deleterious, a crucial issue for melatonin agonist/antagonist drug development and dosing time. We provide a conceptual framework - anchored in the dimension of 'time' - to reconcile paradoxical findings in the literature. We propose that the relative timing between elevated melatonin concentrations and glycemic challenge should be considered to better understand the mechanisms and therapeutic opportunities of melatonin signaling in glycemic health and disease.
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Affiliation(s)
- Marta Garaulet
- Department of Physiology, University of Murcia and Research Biomedical Institute of Murcia, Murcia, Spain; Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Jingyi Qian
- Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jose C Florez
- Department of Medicine, Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | | | - Richa Saxena
- Department of Medicine, Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
| | - Frank A J L Scheer
- Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
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