, Volume 62, Issue 8, pp 1453–1462 | Cite as

Cellular circadian period length inversely correlates with HbA1c levels in individuals with type 2 diabetes

  • Flore Sinturel
  • Anne-Marie Makhlouf
  • Patrick Meyer
  • Christel Tran
  • Zoltan Pataky
  • Alain Golay
  • Guillaume Rey
  • Cédric Howald
  • Emmanouil T. Dermitzakis
  • Claude Pichard
  • Jacques Philippe
  • Steven A. Brown
  • Charna DibnerEmail author



The circadian system plays an essential role in regulating the timing of human metabolism. Indeed, circadian misalignment is strongly associated with high rates of metabolic disorders. The properties of the circadian oscillator can be measured in cells cultured in vitro and these cellular rhythms are highly informative of the physiological circadian rhythm in vivo. We aimed to discover whether molecular properties of the circadian oscillator are altered as a result of type 2 diabetes.


We assessed molecular clock properties in dermal fibroblasts established from skin biopsies taken from nine obese and eight non-obese individuals with type 2 diabetes and 11 non-diabetic control individuals. Following in vitro synchronisation, primary fibroblast cultures were subjected to continuous assessment of circadian bioluminescence profiles based on lentiviral luciferase reporters.


We observed a significant inverse correlation (ρ = −0.592; p < 0.05) between HbA1c values and circadian period length within cells from the type 2 diabetes group. RNA sequencing analysis conducted on samples from this group revealed that ICAM1, encoding the endothelial adhesion protein, was differentially expressed in fibroblasts from individuals with poorly controlled vs well-controlled type 2 diabetes and its levels correlated with cellular period length. Consistent with this circadian link, the ICAM1 gene also displayed rhythmic binding of the circadian locomotor output cycles kaput (CLOCK) protein that correlated with gene expression.


We provide for the first time a potential molecular link between glycaemic control in individuals with type 2 diabetes and circadian clock machinery. This paves the way for further mechanistic understanding of circadian oscillator changes upon type 2 diabetes development in humans.

Data availability

RNA sequencing data and clinical phenotypic data have been deposited at the European Genome-phenome Archive (EGA), which is hosted by the European Bioinformatics Institute (EBI) and the Centre for Genomic Regulation (CRG), ega-box-1210, under accession no. EGAS00001003622.


Circadian bioluminescence recording Circadian clock HbA1c Humans ICAM1 Type 2 diabetes 



Chromatin immunoprecipitation


Circadian locomotor output cycles kaput


Circadian time


Munich Chronotype Questionnaire


O-linked β-N-acetylglucosamine


Quantitative real-time PCR


RNA sequencing


Suprachiasmatic nuclei



The authors thank I. Wagner, L. Perrin (the Dibner lab), G. Sinyavsky (Florida University, USA), K. Tsutsumi and K. Tamura (Yamaguchi University, Japan) for assistance with the experiments and thank J. M. De Abreu Nunes (Department of Genetics and Evolution, University of Geneva) for help with statistical analyses.

Contribution statement

FS, A-MM and CD collected the data and drafted the manuscript. PM, CT and JP recruited and enrolled the volunteers. ZP and AG recruited the volunteers. CH, GR and ETD conducted and analysed RNA sequencing. SAB, CP, JP and CD designed the study. All the authors participated in conception and design of the study and in the drafting and approval of the manuscript. CD is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.


This work was funded by the Novartis Foundation for Medical-Biological Research, Jubiläumsstiftung Swiss Life Foundation, Vontobel Foundation and Olga Mayenfisch Foundation (CD) and by SNSF Sinergia grant CRSII3_160741 (SAB, JP, ETD).

Compliance with ethical standards

Duality of interest

The authors declare that there is no duality of interest associated with this manuscript.

Supplementary material

125_2019_4907_MOESM1_ESM.pdf (481 kb)
ESM 1 (PDF 481 kb)


  1. 1.
    Partch CL, Green CB, Takahashi JS (2014) Molecular architecture of the mammalian circadian clock. Trends Cell Biol 24(2):90–99. CrossRefPubMedGoogle Scholar
  2. 2.
    Gachon F, Loizides-Mangold U, Petrenko V, Dibner C (2017) Glucose homeostasis: regulation by peripheral circadian clocks in rodents and humans. Endocrinology 158(5):1074–1084. CrossRefPubMedGoogle Scholar
  3. 3.
    Marcheva B, Ramsey KM, Buhr ED et al (2010) Disruption of the clock components CLOCK and BMAL1 leads to hypoinsulinaemia and diabetes. Nature 466(7306):627–631. CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Perelis M, Marcheva B, Ramsey KM et al (2015) Pancreatic beta cell enhancers regulate rhythmic transcription of genes controlling insulin secretion. Science 350(6261):aac4250. CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Dibner C, Schibler U (2015) Circadian timing of metabolism in animal models and humans. J Intern Med 277(5):513–527. CrossRefPubMedGoogle Scholar
  6. 6.
    Pulimeno P, Mannic T, Sage D et al (2013) Autonomous and self-sustained circadian oscillators displayed in human islet cells. Diabetologia 56(3):497–507. CrossRefPubMedGoogle Scholar
  7. 7.
    Saini C, Petrenko V, Pulimeno P et al (2016) A functional circadian clock is required for proper insulin secretion by human pancreatic islet cells. Diabetes Obes Metab 18(4):355–365. CrossRefPubMedGoogle Scholar
  8. 8.
    Englund A, Kovanen L, Saarikoski ST et al (2009) NPAS2 and PER2 are linked to risk factors of the metabolic syndrome. J Circadian Rhythms 7(0):5. CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    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(1):82–88. CrossRefGoogle Scholar
  10. 10.
    Perrin L, Loizides-Mangold U, Skarupelova S et al (2015) Human skeletal myotubes display a cell-autonomous circadian clock implicated in basal myokine secretion. Mol Metab 4(11):834–845. CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Brown SA, Fleury-Olela F, Nagoshi E et al (2005) The period length of fibroblast circadian gene expression varies widely among human individuals. PLoS Biol 3(10):e338. CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Brown SA, Kunz D, Dumas A et al (2008) Molecular insights into human daily behavior. Proc Natl Acad Sci U S A 105(5):1602–1607. CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Saini C, Brown SA, Dibner C (2015) Human peripheral clocks: applications for studying circadian phenotypes in physiology and pathophysiology. Front Neurol 6:95PubMedPubMedCentralGoogle Scholar
  14. 14.
    Roenneberg T, Wirz-Justice A, Merrow M (2003) Life between clocks: daily temporal patterns of human chronotypes. J Biol Rhythm 18(1):80–90. CrossRefGoogle Scholar
  15. 15.
    Toledo JR, Prieto Y, Oramas N, Sanchez O (2009) Polyethylenimine-based transfection method as a simple and effective way to produce recombinant lentiviral vectors. Appl Biochem Biotechnol 157(3):538–544. CrossRefPubMedGoogle Scholar
  16. 16.
    Marco-Sola S, Sammeth M, Guigó R, Ribeca P (2012) The GEM mapper: fast, accurate and versatile alignment by filtration. Nat Methods 9(12):1185–1188. CrossRefPubMedGoogle Scholar
  17. 17.
    Mannic T, Meyer P, Triponez F et al (2013) Circadian clock characteristics are altered in human thyroid malignant nodules. J Clin Endocrinol Metab 98(11):4446–4456. CrossRefPubMedGoogle Scholar
  18. 18.
    Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol 57(1):289–300Google Scholar
  19. 19.
    Cleveland WS (1981) LOWESS: a program for smoothing scatterplots by robust locally weighted regression. Am Stat 35(1):54. CrossRefGoogle Scholar
  20. 20.
    Derosa G, Maffioli P (2016) A review about biomarkers for the investigation of vascular function and impairment in diabetes mellitus. Vasc Health Risk Manag 12:415–419. CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Perrin L, Loizides-Mangold U, Chanon S et al (2018) Transcriptomic analyses reveal rhythmic and CLOCK-driven pathways in human skeletal muscle. Elife 7:e34114.
  22. 22.
    Gao Y, Meng D, Sun N et al (2014) Clock upregulates intercellular adhesion molecule-1 expression and promotes mononuclear cells adhesion to endothelial cells. Biochem Biophys Res Commun 443(2):586–591. CrossRefPubMedGoogle Scholar
  23. 23.
    Wang Q, Bozack SN, Yan Y, Boulton ME, Grant MB, Busik JV (2014) Regulation of retinal inflammation by rhythmic expression of MiR-146a in diabetic retina. Invest Ophthalmol Vis Sci 55(6):3986–3994. CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Ramakrishnan SK, Zhang H, Takahashi S et al (2016) HIF2alpha is an essential molecular brake for postprandial hepatic glucagon response independent of insulin signaling. Cell Metab 23(3):505–516. CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Kaasik K, Kivimae S, Allen JJ et al (2013) Glucose sensor O-GlcNAcylation coordinates with phosphorylation to regulate circadian clock. Cell Metab 17(2):291–302. CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Wei K, Piecewicz SM, McGinnis LM et al (2013) A liver Hif-2alpha-Irs2 pathway sensitizes hepatic insulin signaling and is modulated by Vegf inhibition. Nat Med 19(10):1331–1337. CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Gomez-Abellan P, Gomez-Santos C, Madrid JA et al (2010) Circadian expression of adiponectin and its receptors in human adipose tissue. Endocrinology 151(1):115–122. CrossRefPubMedGoogle Scholar
  28. 28.
    Otway DT, Mantele S, Bretschneider S et al (2011) Rhythmic diurnal gene expression in human adipose tissue from individuals who are lean, overweight, and type 2 diabetic. Diabetes 60(5):1577–1581. CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Flore Sinturel
    • 1
    • 2
    • 3
    • 4
  • Anne-Marie Makhlouf
    • 1
    • 2
    • 3
    • 4
  • Patrick Meyer
    • 1
  • Christel Tran
    • 1
    • 5
  • Zoltan Pataky
    • 6
  • Alain Golay
    • 6
  • Guillaume Rey
    • 3
    • 4
    • 7
  • Cédric Howald
    • 4
    • 7
  • Emmanouil T. Dermitzakis
    • 3
    • 4
    • 7
  • Claude Pichard
    • 1
  • Jacques Philippe
    • 1
    • 3
  • Steven A. Brown
    • 8
  • Charna Dibner
    • 1
    • 2
    • 3
    • 4
    Email author
  1. 1.Department of Medicine, Division of Endocrinology, Diabetes, Hypertension and Nutrition, Faculty of MedicineUniversity of GenevaGenevaSwitzerland
  2. 2.Department of Cell Physiology and Metabolism, Faculty of MedicineUniversity of GenevaGenevaSwitzerland
  3. 3.Diabetes Center, Faculty of MedicineUniversity of GenevaGenevaSwitzerland
  4. 4.Institute of Genetics and Genomics of Geneva (iGE3)University of GenevaGenevaSwitzerland
  5. 5.Center for Molecular Diseases, Division of Genetic MedicineLausanne University HospitalLausanneSwitzerland
  6. 6.Division for Therapeutic Patient Education for Chronic DiseasesUniversity Hospital of GenevaGenevaSwitzerland
  7. 7.Department of Genetic Medicine and Development, Faculty of MedicineUniversity of GenevaGenevaSwitzerland
  8. 8.Institute of Pharmacology and ToxicologyUniversity of ZurichZurichSwitzerland

Personalised recommendations