Skip to main content
Top
Published in: Diabetologia 5/2015

01-05-2015 | Article

Season-dependent associations of circadian rhythm-regulating loci (CRY1, CRY2 and MTNR1B) and glucose homeostasis: the GLACIER Study

Authors: Frida Renström, Robert W. Koivula, Tibor V. Varga, Göran Hallmans, Hindrik Mulder, Jose C. Florez, Frank B. Hu, Paul W. Franks

Published in: Diabetologia | Issue 5/2015

Login to get access

Abstract

Aims/hypothesis

The association of single nucleotide polymorphisms (SNPs) proximal to CRY2 and MTNR1B with fasting glucose is well established. CRY1/2 and MTNR1B encode proteins that regulate circadian rhythmicity and influence energy metabolism. Here we tested whether season modified the relationship of these loci with blood glucose concentration.

Methods

SNPs rs8192440 (CRY1), rs11605924 (CRY2) and rs10830963 (MTNR1B) were genotyped in a prospective cohort study from northern Sweden (n = 16,499). The number of hours of daylight exposure during the year ranged from 4.5 to 22 h daily. Owing to the non-linear distribution of daylight throughout the year, season was dichotomised based on the vernal and autumnal equinoxes. Effect modification was assessed using linear regression models fitted with a SNP × season interaction term, marginal effect terms and putative confounding variables, with fasting or 2 h glucose concentrations as outcomes.

Results

The rs8192440 (CRY1) variant was only associated with fasting glucose among participants (n = 2,318) examined during the light season (β = −0.04 mmol/l per A allele, 95% CI −0.08, −0.01, p = 0.02, p interaction = 0.01). In addition to the established association with fasting glucose, the rs11605924 (CRY2) and rs10830963 (MTNR1B) loci were associated with 2 h glucose concentrations (β = 0.07 mmol/l per A allele, 95% CI 0.03, 0.12, p = 0.0008, n = 9,605, and β = −0.11 mmol/l per G allele, 95% CI −0.15, −0.06, p < 0.0001, n = 9,517, respectively), but only in participants examined during the dark season (p interaction = 0.006 and 0.04, respectively). Repeated measures analyses including data collected 10 years after baseline (n = 3,500) confirmed the results for the CRY1 locus (p interaction = 0.01).

Conclusions/interpretation

In summary, these observations suggest a biologically plausible season-dependent association between SNPs at CRY1, CRY2 and MTNR1B and glucose homeostasis.
Literature
1.
go back to reference Dupuis J, Langenberg C, Prokopenko I et al (2010) New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 42:105–116CrossRefPubMedCentralPubMed Dupuis J, Langenberg C, Prokopenko I et al (2010) New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 42:105–116CrossRefPubMedCentralPubMed
3.
go back to reference Scheer FA, Hilton MF, Mantzoros CS, Shea SA (2009) Adverse metabolic and cardiovascular consequences of circadian misalignment. Proc Natl Acad Sci U S A 106:4453–4458CrossRefPubMedCentralPubMed Scheer FA, Hilton MF, Mantzoros CS, Shea SA (2009) Adverse metabolic and cardiovascular consequences of circadian misalignment. Proc Natl Acad Sci U S A 106:4453–4458CrossRefPubMedCentralPubMed
4.
go back to reference Delezie J, Challet E (2011) Interactions between metabolism and circadian clocks: reciprocal disturbances. Ann N Y Acad Sci 1243:30–46CrossRefPubMed Delezie J, Challet E (2011) Interactions between metabolism and circadian clocks: reciprocal disturbances. Ann N Y Acad Sci 1243:30–46CrossRefPubMed
5.
go back to reference Karlsson B, Knutsson A, Lindahl B (2001) Is there an association between shift work and having a metabolic syndrome? Results from a population based study of 27,485 people. Occup Environ Med 58:747–752CrossRefPubMedCentralPubMed Karlsson B, Knutsson A, Lindahl B (2001) Is there an association between shift work and having a metabolic syndrome? Results from a population based study of 27,485 people. Occup Environ Med 58:747–752CrossRefPubMedCentralPubMed
6.
go back to reference Scott RA, Lagou V, Welch RP et al (2012) Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet 44:991–1005CrossRefPubMedCentralPubMed Scott RA, Lagou V, Welch RP et al (2012) Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet 44:991–1005CrossRefPubMedCentralPubMed
7.
go back to reference Stamenkovic JA, Olsson AH, Nagorny CL et al (2012) Regulation of core clock genes in human islets. Metab Clin Exp 61:978–985CrossRefPubMed Stamenkovic JA, Olsson AH, Nagorny CL et al (2012) Regulation of core clock genes in human islets. Metab Clin Exp 61:978–985CrossRefPubMed
8.
go back to reference Zhang EE, Liu Y, Dentin R et al (2010) Cryptochrome mediates circadian regulation of cAMP signaling and hepatic gluconeogenesis. Nat Med 16:1152–1156CrossRefPubMedCentralPubMed Zhang EE, Liu Y, Dentin R et al (2010) Cryptochrome mediates circadian regulation of cAMP signaling and hepatic gluconeogenesis. Nat Med 16:1152–1156CrossRefPubMedCentralPubMed
9.
go back to reference Barclay JL, Shostak A, Leliavski A et al (2013) High-fat diet-induced hyperinsulinemia and tissue-specific insulin resistance in Cry-deficient mice. Am J Physiol Endocrinol Metab 304:E1053–E1063CrossRefPubMed Barclay JL, Shostak A, Leliavski A et al (2013) High-fat diet-induced hyperinsulinemia and tissue-specific insulin resistance in Cry-deficient mice. Am J Physiol Endocrinol Metab 304:E1053–E1063CrossRefPubMed
10.
go back to reference Griebel G, Ravinet-Trillou C, Beeske S, Avenet P, Pichat P (2014) Mice deficient in cryptochrome 1 (cry1 (-/-)) exhibit resistance to obesity induced by a high-fat diet. Front Endocrinol 5:49CrossRef Griebel G, Ravinet-Trillou C, Beeske S, Avenet P, Pichat P (2014) Mice deficient in cryptochrome 1 (cry1 (-/-)) exhibit resistance to obesity induced by a high-fat diet. Front Endocrinol 5:49CrossRef
11.
go back to reference Renström F, Shungin D, Johansson I et al (2011) Genetic predisposition to long-term nondiabetic deteriorations in glucose homeostasis: ten-year follow-up of the GLACIER study. Diabetes 60:345–354CrossRefPubMedCentralPubMed Renström F, Shungin D, Johansson I et al (2011) Genetic predisposition to long-term nondiabetic deteriorations in glucose homeostasis: ten-year follow-up of the GLACIER study. Diabetes 60:345–354CrossRefPubMedCentralPubMed
12.
go back to reference Kurbasic A, Poveda A, Chen Y et al (2014) Gene-lifestyle interactions in complex diseases: design and description of the GLACIER and VIKING studies. Curr Nutr Rep 3:400–411CrossRefPubMed Kurbasic A, Poveda A, Chen Y et al (2014) Gene-lifestyle interactions in complex diseases: design and description of the GLACIER and VIKING studies. Curr Nutr Rep 3:400–411CrossRefPubMed
13.
go back to reference Hallmans G, Ågren A, Johansson G et al (2003) Cardiovascular disease and diabetes in the Northern Sweden Health and Disease Study Cohort—evaluation of risk factors and their interactions. Scand J Public Health Suppl 61:18–24CrossRefPubMed Hallmans G, Ågren A, Johansson G et al (2003) Cardiovascular disease and diabetes in the Northern Sweden Health and Disease Study Cohort—evaluation of risk factors and their interactions. Scand J Public Health Suppl 61:18–24CrossRefPubMed
14.
go back to reference World Health Organization (1999) Definitions, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus. World Health Organization, Geneva World Health Organization (1999) Definitions, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus. World Health Organization, Geneva
16.
go back to reference Johansson I, Hallmans G, Wikman A, Biessy C, Riboli E, Kaaks R (2002) Validation and calibration of food-frequency questionnaire measurements in the Northern Sweden Health and Disease cohort. Public Health Nutr 5:487–496CrossRefPubMed Johansson I, Hallmans G, Wikman A, Biessy C, Riboli E, Kaaks R (2002) Validation and calibration of food-frequency questionnaire measurements in the Northern Sweden Health and Disease cohort. Public Health Nutr 5:487–496CrossRefPubMed
17.
go back to reference InterAct C (2012) Validity of a short questionnaire to assess physical activity in 10 European countries. Eur J Epidemiol 27:15–25CrossRef InterAct C (2012) Validity of a short questionnaire to assess physical activity in 10 European countries. Eur J Epidemiol 27:15–25CrossRef
18.
go back to reference Voight BF, Kang HM, Ding J et al (2012) The MetaboChip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits. PLoS Genet 8:e1002793CrossRefPubMedCentralPubMed Voight BF, Kang HM, Ding J et al (2012) The MetaboChip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits. PLoS Genet 8:e1002793CrossRefPubMedCentralPubMed
19.
go back to reference Ikeda H, Yong Q, Kurose T et al (2007) Clock gene defect disrupts light-dependency of autonomic nerve activity. Biochem Biophys Res Commun 364:457–463CrossRefPubMed Ikeda H, Yong Q, Kurose T et al (2007) Clock gene defect disrupts light-dependency of autonomic nerve activity. Biochem Biophys Res Commun 364:457–463CrossRefPubMed
20.
go back to reference Thresher RJ, Vitaterna MH, Miyamoto Y et al (1998) Role of mouse cryptochrome blue-light photoreceptor in circadian photoresponses. Science 282:1490–1494CrossRefPubMed Thresher RJ, Vitaterna MH, Miyamoto Y et al (1998) Role of mouse cryptochrome blue-light photoreceptor in circadian photoresponses. Science 282:1490–1494CrossRefPubMed
21.
go back to reference Vitaterna MH, Selby CP, Todo T et al (1999) Differential regulation of mammalian period genes and circadian rhythmicity by cryptochromes 1 and 2. Proc Natl Acad Sci U S A 96:12114–12119CrossRefPubMedCentralPubMed Vitaterna MH, Selby CP, Todo T et al (1999) Differential regulation of mammalian period genes and circadian rhythmicity by cryptochromes 1 and 2. Proc Natl Acad Sci U S A 96:12114–12119CrossRefPubMedCentralPubMed
22.
go back to reference von Gall C, Stehle JH, Weaver DR (2002) Mammalian melatonin receptors: molecular biology and signal transduction. Cell Tissue Res 309:151–162CrossRef von Gall C, Stehle JH, Weaver DR (2002) Mammalian melatonin receptors: molecular biology and signal transduction. Cell Tissue Res 309:151–162CrossRef
23.
go back to reference Lyssenko V, Nagorny CL, Erdos MR et al (2009) Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nat Genet 41:82–88CrossRefPubMedCentralPubMed Lyssenko V, Nagorny CL, Erdos MR et al (2009) Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nat Genet 41:82–88CrossRefPubMedCentralPubMed
24.
go back to reference Nagorny CL, Sathanoori R, Voss U, Mulder H, Wierup N (2011) Distribution of melatonin receptors in murine pancreatic islets. J Pineal Res 50:412–417CrossRefPubMed Nagorny CL, Sathanoori R, Voss U, Mulder H, Wierup N (2011) Distribution of melatonin receptors in murine pancreatic islets. J Pineal Res 50:412–417CrossRefPubMed
25.
go back to reference Mussig K, Staiger H, Machicao F, Haring HU, Fritsche A (2010) Genetic variants in MTNR1B affecting insulin secretion. Ann Med 42:387–393CrossRefPubMed Mussig K, Staiger H, Machicao F, Haring HU, Fritsche A (2010) Genetic variants in MTNR1B affecting insulin secretion. Ann Med 42:387–393CrossRefPubMed
27.
go back to reference Bouatia-Naji N, Bonnefond A, Cavalcanti-Proenca C et al (2009) A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk. Nat Genet 41:89–94CrossRefPubMed Bouatia-Naji N, Bonnefond A, Cavalcanti-Proenca C et al (2009) A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk. Nat Genet 41:89–94CrossRefPubMed
28.
go back to reference Simonis-Bik AM, Nijpels G, van Haeften TW et al (2010) Gene variants in the novel type 2 diabetes loci CDC123/CAMK1D, THADA, ADAMTS9, BCL11A, and MTNR1B affect different aspects of pancreatic beta-cell function. Diabetes 59:293–301CrossRefPubMedCentralPubMed Simonis-Bik AM, Nijpels G, van Haeften TW et al (2010) Gene variants in the novel type 2 diabetes loci CDC123/CAMK1D, THADA, ADAMTS9, BCL11A, and MTNR1B affect different aspects of pancreatic beta-cell function. Diabetes 59:293–301CrossRefPubMedCentralPubMed
29.
go back to reference Kemp DM, Ubeda M, Habener JF (2002) Identification and functional characterization of melatonin Mel 1a receptors in pancreatic beta cells: potential role in incretin-mediated cell function by sensitization of cAMP signaling. Mol Cell Endocrinol 191:157–166CrossRefPubMed Kemp DM, Ubeda M, Habener JF (2002) Identification and functional characterization of melatonin Mel 1a receptors in pancreatic beta cells: potential role in incretin-mediated cell function by sensitization of cAMP signaling. Mol Cell Endocrinol 191:157–166CrossRefPubMed
30.
go back to reference Bonnefond A, Clement N, Fawcett K et al (2012) Rare MTNR1B variants impairing melatonin receptor 1B function contribute to type 2 diabetes. Nat Genet 44:297–301CrossRefPubMedCentralPubMed Bonnefond A, Clement N, Fawcett K et al (2012) Rare MTNR1B variants impairing melatonin receptor 1B function contribute to type 2 diabetes. Nat Genet 44:297–301CrossRefPubMedCentralPubMed
31.
go back to reference Waldhauser F, Dietzel M (1985) Daily and annual rhythms in human melatonin secretion: role in puberty control. Ann N Y Acad Sci 453:205–214CrossRefPubMed Waldhauser F, Dietzel M (1985) Daily and annual rhythms in human melatonin secretion: role in puberty control. Ann N Y Acad Sci 453:205–214CrossRefPubMed
Metadata
Title
Season-dependent associations of circadian rhythm-regulating loci (CRY1, CRY2 and MTNR1B) and glucose homeostasis: the GLACIER Study
Authors
Frida Renström
Robert W. Koivula
Tibor V. Varga
Göran Hallmans
Hindrik Mulder
Jose C. Florez
Frank B. Hu
Paul W. Franks
Publication date
01-05-2015
Publisher
Springer Berlin Heidelberg
Published in
Diabetologia / Issue 5/2015
Print ISSN: 0012-186X
Electronic ISSN: 1432-0428
DOI
https://doi.org/10.1007/s00125-015-3533-8

Other articles of this Issue 5/2015

Diabetologia 5/2015 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.