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Dental and Medical Problems

2024, vol. 61, nr 3, May-June, p. 465–469

doi: 10.17219/dmp/185718

Publication type: research letter

Language: English

License: Creative Commons Attribution 3.0 Unported (CC BY 3.0)

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Karuga FF, Jaromirska J, Sochal M, Białasiewicz P, Gabryelska A. Association between glucose metabolism, the circadian cycle and hypoxia: Evaluation of the NPAS2 and Rev-Erb-α protein serum levels in obstructive sleep apnea patients – a pilot study. Dent Med Probl. 2024;61(3):463–467. doi:10.17219/dmp/185718

Association between glucose metabolism, the circadian cycle and hypoxia: Evaluation of the NPAS2 and Rev-Erb-α protein serum levels in obstructive sleep apnea patients – a pilot study

Filip Franciszek Karuga1,2,A,B,C,D,E,F, Julia Jaromirska1,D,E,F, Marcin Sochal1,B,E,F, Piotr Białasiewicz1,E,F, Agata Gabryelska1,A,B,C,D,E,F

1 Department of Sleep Medicine and Metabolic Disorders, Medical University of Lodz, Poland

2 Department of Gynecology, Oncological Gynecology and Treatment of Endometriosis, Polish Mother’s Memorial Hospital – Research Institute, Lodz, Poland

Graphical abstract


Graphical abstracts

Abstract

Background. Obstructive sleep apnea (OSA) is one of the risk factors for diabetes mellitus type 2 (DM2). As OSA is associated with the disruption of the circadian rhythm, it affects circadian clock proteins, including neuronal PAS domain protein 2 (NPAS2) and nuclear receptor subfamily 1 group D member 1 (Rev-Erb-α). These proteins have been shown to be related to metabolic abnormalities, i.a., insulin resistance.

Objectives. The present pilot study aimed to investigate the NPAS2 and Rev-Erb-α protein serum levels in the groups of patients with severe OSA and severe OSA+DM2 in comparison with healthy controls, taking into account correlations with polysomnography (PSG) parameters (e.g., oxygen saturation (SpO2) variables).

Material and methods. A total of 40 participants were included in the study. They were split into 3 groups as follows: the OSA group (n = 17; apnea–hypopnea index (AHI) >30, no DM2); the OSA+DM2 group (n = 7; AHI > 30 and DM2); and the control group (n = 16; AHI < 5, no DM2). All participants underwent a nocturnal PSG examination and had their blood collected the following morning. The serum levels of NPAS2 and Rev-Erb-α proteins were assessed using the enzyme-linked immunosorbent assay (ELISA).

Results. The mean NPAS2 protein level was significantly lower in the OSA group as compared to healthy individuals (p = 0.017). Additionally, the OSA group presented with lower NPAS2 protein levels as compared to the OSA+DM2 group, but only a tendency was observed (p = 0.094). No differences in the Rev-Erb-α protein concentration were noticed. Furthermore, a negative correlation between AHI during rapid eye movement (REM) sleep and the NPAS2 protein serum level was observed (r = −0.478; p = 0.002).

Conclusions. Serum NPAS2 protein might be involved in metabolic dysregulation present among OSA patients, while the mechanism itself may be associated with REM sleep.

Keywords: hypoxia, circadian cycle, glucose metabolism, NPAS2, Rev-Erb-α

Introduction

Obstructive sleep apnea (OSA) is characterized by recurrent pauses in breathing during sleep, leading to intermittent hypoxia, arousal and sleep fragmenta­tion.1 The gold standard in the OSA diagnosis is a polysomnography (PSG) examination, which enables the assessment of OSA severity through the apnea–hypopnea index (AHI).2 The available literature recognizes OSA as an independent risk factor for various comorbidities, including glucose metabolism impairment, insulin resistance and diabetes mellitus type 2 (DM2).3, 4 These metabolic complications can be related to electrolyte and vitamin dysregulation,5 serotoninergic system dysregulation6, 7, 8 or the alteration of circulating adipokines.9

Circadian clocks are endogenous coordinators of the 24-hour rhythm of behavioral and molecular processes.10 Each circadian clock comprises a set of genes that function as activators, namely circadian locomotor output cycles kaput (CLOCK) and basic helix–loop–helix ARNT-like (BMAL1).11 Through binding to regulatory elements containing E-boxes, they activate the transcription of repressor proteins period (encoded by Per) and cryptochrome (encoded by Cry).12 Neuronal PAS domain protein 2 (NPAS2), similar to circadian clock activators and hypoxia-inducible factors, belongs to the helix–loop–helix Per/Armt/Sim (PAS) transcription factor family. Due to this structural similarity, it can substitute the function of CLOCK.13 In mice, which serve as a mammalian model of the circadian clock,14 the activation of CLOCK–BMAL1 occurs in the daytime, which sub­sequently causes the transcription of both Per and Cry in the afternoon, and the accumulation of PER and CRY proteins in the evening. The proteins trans­locate to the nucleus at nighttime and interact with the CLOCK–BMAL1 complex, which results in the repression of their transcription. Following a decrease in the protein concentration at night, the CLOCK–BMAL1 complex starts a new cycle in the morning.15 The regulatory complex of the circadian clock also includes a supporting loop that involves nuclear receptor subfamily 1 group D member 1 (Rev-Erb-α), which interacts with the CLOCK–BMAL1 complex, taking part in the interlocked feedback loops of activators and repressors, thereby creating a canonical positive- and negative-feedback gene network.16 Studies have shown that the dysregulation of the circadian clock can result in metabolic complications, including glucose metabolism impairment.17

Therefore, this pilot study aimed to investigate the NPAS2 and Rev-Erb-α protein serum levels in patients with severe OSA, severe OSA and DM2, and in healthy individuals, and to assess their relationship with PSG parameters.

Material and methods

This cross-sectional study was conducted at the Department of Sleep Medicine and Metabolic Disorders of the Medical University of Lodz, Poland, between January and June 2021 – recruitment and data collection. Patients were recruited according to the inclusion criteria (age above 18 and below 70 years, body mass index (BMI) of 20–40 kg/m2, and providing informed written consent to participate in the study). The exclusion criteria comprised withdrawing of the consent, chronic respiratory diseases, chronic inflammatory diseases, infection within 1 month of blood collection, active cancer or a history of cancer, a lifetime history of diagnosed sleep disorders other than OSA, employment in the changing shift system, caffeine intake >900 mg per day, and the use of hypnotic medications or any medications known to affect sleep during 2 weeks before the sleep laboratory examination. Patients referred with suspected OSA syndrome underwent a standard medical examination and a nocturnal PSG examination. The DM2 diagnosis was based on the patient’s medical history. After the examination, venous blood samples were collected into serum separator blood collection tubes. Forty participants were qualified for the study. Based on the PSG and clinical data, the participants were assigned to one of 3 study groups: OSA (severe OSA – AHI > 30, no DM2); OSA+DM2 (severe OSA – AHI > 30 and DM2); and control (no OSA – AHI < 5, no DM2). The study was approved by the Bioethical Committee of the Medical University of Lodz (RNN/432/18/KE).

Polysomnography

The patients were admitted to the sleep laboratory at about 9 p.m. (±0.5 h), where standard physical and subjective examinations were conducted, and body mass, height, blood pressure, and pulse were measured. Standard nocturnal PSG was performed by recording the following channels: electroencephalography (EEG) (C4\A1, C3\A2); electromyography (EMG) of the chin muscles and tibialis anterior; electrooculography (EOG); measurements of the oronasal airflow (a thermistor gauge); snor­ing; body position; respiratory movements of the chest and the abdomen (piezoelectric gauges); unipolar electro­cardiogram (ECG); and hemoglobin oxygen saturation (SpO2) (Alice 6; Phillips Respironics, Murrysville, USA). Polysomnographic events were scored by the same expe­rienced physician. Sleep stages were scored according to the criteria based on the 30-second epoch standard.2

Biochemical analysis

Peripheral blood samples were collected in the morning following PSG (between 6 a.m. and 7 a.m., within 10 min of awakening) into blood collection tubes with a clot activator and ethylenediaminetetraacetic acid (EDTA). Blood samples with a clot activator were centrifuged immediately after blood draws at 4°C. Serum was collected and stored at −80°C. The serum protein concentration was assessed using an enzyme-linked immunosorbent assay (ELISA) kit (EIAaB, Wuhan, China) and the absorbance was measured at wavelength λ = 450 nm, using an absorbance reader (BioTek 800 TS; Agilent Technologies Inc., Santa Clara, USA).

Statistical analysis

Statistical analysis was conducted with the use of Statistica 13 PL (StatSoft Polska, Krakow, Poland). The assessment of distribution (normal/non-normal) for continuous variables was performed with the Shapiro–Wilk test. Parametric independent variables were assessed with Student’s t test, and the Mann–Whitney U test was used for nonparametric independent variables. Spearman’s correlation test was applied for correlations. A p-value <0.05 was considered statistically significant.

Results

The baseline characteristics of the pilot study participants are shown in Table 1, and the results, including the serum levels of NPAS2 and Rev-Erb-α proteins, are presented in Table 2. No statistically significant differences were noticed in the Rev-Erb-α protein concentration among all study groups (p = 0.624). The mean NPAS2 protein level was significantly lower in the OSA group as compared to healthy individuals (p = 0.017). Additionally, the OSA group presented with lower NPAS2 protein levels as compared to the OSA+DM2 group, but only a trend was observed, as the difference did not reach statistical significance (p = 0.094). Of the evaluated correlations, only a weak negative correlation between AHI during rapid eye movement (REM) sleep and the NPAS2 protein serum level was observed (r = −0.478; p = 0.002).

Discussion

The dysregulation of circadian clock genes has been shown to cause not only sleep disorders, such as sleep phase syndrome,18 but also metabolic abnormalities, including metabolic syndrome19 or insulin resistance.20 Zhang et al. revealed that diabetic rats had significantly higher Rev-Erb-α protein levels in adipose tissue as compared to nondiabetic rats.21 Their work suggests that Rev-Erb-α may be one of the key molecules potentially causing metabolic syndromes through circadian clock disruption.21 Additionally, in a study by Kooner et al., which included 5,561 patients with DM2, NPAS2 genes were also associated with the development of DM2.22 Literature concerning circadian clock disruption among patients suffering from OSA is limited, both in terms of number of publications and only several circadian clock genes being investigated.23 Canales et al., in a cross-sectional study on 49 patients, compared groups with OSA or nocturnal hypoxemia (defined as ≥10% of total sleep time (TST) spent at SpO2 < 90%) to those without such conditions, and found that the mRNA expression of Rev-Erb-α and NPAS2 was reduced in patients with nocturnal hypoxemia.24 Nevertheless, the study was a sub-analysis of a cohort suffering from severe kidney dysfunction. Since it has been established that kidney function greatly influences the expression of circadian clock genes,25 it is impossible to state whether OSA severity, hypoxia or kidney dysfunction had a key impact on the obtained results.

Our results from a pilot study show the same tendency as reported in research by Xie et al., where NPAS2 gene expression was decreased in untreated OSA patients with AHI > 15.26 However, their results did not present statistical significance, contrary to our study, where the difference in the NPAS2 protein levels between the OSA group and the control group was significant (p = 0.017). Extended research that would include both NPAS2 gene expression and protein level, together with CLOCK–BMAL1 investigations, might help define exact relationships between circadian clock activators in response to hypoxia occurring in the REM phase.

Limitations

Our study has its limitations, including a small sample size (only 40 participants). We aimed to conduct a small-scale study to test the research design and feasibility to obtain significant results, which was achieved. Therefore, we stand prepared to expand the investigation. As the research was conducted as a pilot study and the group of participants was small, it was hard to choose subjects that would perfectly match all parameters; thus, the age of the subjects varied. Another limitation that should be mentioned are the conditions in which the study was conducted, namely sleeping in the hospital PSG laboratory; TST might have been influenced more by the attitude and the psychological aspects of adjusting to a new sleep environment than by typical circadian-related difficulties in falling asleep.

Conclusions

Serum NPAS2 protein might be involved in metabolic dysregulation present among OSA patients, while the mechanism itself may be associated with REM sleep. The findings of our pilot study may help better understand the molecular mechanism responsible for circadian cycles, the reaction to hypoxia, and their influence on disturbances of glucose metabolism, as well as interactions between them. However, to confirm the role of NPAS2 and Rev-Erb-α in the development of DM2, the continuation of the study is necessary.

Ethics approval and consent to participate

The study was approved by the Bioethical Committee of the Medical University of Lodz, Poland (RNN/432/18/K). All subjects provided informed written consent to participate in the study.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Consent for publication

Not applicable.

Tables


Table 1. Baseline characteristics of the study population

Parameter

OSA group
(n = 17)

OSA+DM2 group
(n = 7)

Control group
(n = 16)

p-value

Age [years]
Me (IQR)

53
(44.50–59.50)

64
(56.00–72.00)

46
(33.75–56.50)

0.003*

Sex
n (%)

M

14 (82.35)

6 (85.71)

11 (68.75)

0.548

F

3 (17.65)

1 (14.29)

5 (31.25)

BMI [kg/m2]
Me (IQR)

33.95
(30.99–37.54)

35.89
(32.08–42.67)

27.33
(24.27–28.88)

<0.001*

TST [h]
Me (IQR)

6.50
(6.10–7.08)

5.46
(5.20–6.40)

6.20
(5.70–6.47)

0.050

Arousal index [events/h]
Me (IQR)

23.70
(19.60–28.75)

28.10
(20.90–38.60)

12.25
(7.07–17.30)

<0.001*

AHI in REM sleep [events/h]
Me (IQR)

38.97
(24.44–53.01)

47.51
(29.14–73.88)

1.64
(0.00–7.70)

<0.001*

AHI in NREM sleep [events/h]
Me (IQR)

38.58
(32.33–61.15)

45.66
(35.69–62.89)

1.06
(0.35–1.64)

<0.001*

Total AHI [events/h]
Me (IQR)

51.40
(35.9–64.15)

51.70
(45.70–63.40)

1.45
(0.52–3.00)

<0.001*

Desaturation index [events/h]
Me (IQR)

50.0
(34.8–76.1)

60.0
(51.2–63.0)

2.0
(1.0–3.0)

<0.001*

SpO2 during desaturation events [%]
Me (IQR)

86.9
(80.5–90.1)

87.0
(83.8–88.0)

91.8
(90.5–93.1)

<0.001*

Me – median; IQR – interquartile range; OSA – obstructive sleep apnea; DM2 – diabetes mellitus type 2; M – male; F – female; BMI – body mass index; TST – total sleep time; AHI – apnea–hypopnea index; REM – rapid eye movement; NREM – non-rapid eye movement; SpO2 – oxygen saturation; * statistically significant.
Table 2. Concentrations of circadian clock proteins

Parameter

OSA
group
(n = 17)

OSA+DM2 group
(n = 7)

Control group
(n = 16)

p-value

NPAS2 level
[ng/mL]

117.07 ±55.29

198.28 ±259.83

186.22 ±166.31

0.037*
0.017*a
0.446b
0.094c

Rev-Erb-α level
[ng/mL]

240.93 ±73.46

271.31 ±89.66

272.04 ±92.81

0.624
0.368a
0.947b
0.505c

Data presented as mean ± standard deviation (M ±SD).
NPAS2 – neuronal PAS domain protein 2; Rev-Erb-α – nuclear receptor subfamily 1 group D member 1; * statistically significant (a control group vs. OSA group, b control group vs. OSA+DM2 group, c OSA group vs. OSA+DM2 group).

References (26)

  1. Lévy P, Kohler M, McNicholas WT, et al. Obstructive sleep apnoea syndrome. Nat Rev Dis Primers. 2015;1:15015. doi:10.1038/nrdp.2015.15
  2. Kapur VK, Auckley DH, Chowdhuri S, et al. Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea: An American Academy of Sleep Medicine clinical practice guideline. J Clin Sleep Med. 2017;13(3):479–504. doi:10.5664/jcsm.6506
  3. Hamilton GS, Naughton MT. Impact of obstructive sleep apnoea on diabetes and cardiovascular disease. Med J Aust. 2013;199(8):S27–S30. doi:10.5694/mja13.10579
  4. Kim T, Kang J. Relationship between obstructive sleep apnea, insulin resistance, and metabolic syndrome: A nationwide population-based survey. Endocr J. 2023;70(1):107–119. doi:10.1507/endocrj.EJ22-0280
  5. Kanclerska J, Wieckiewicz M, Nowacki D, et al. Sleep architecture and vitamin D in hypertensives with obstructive sleep apnea: A polysomnographic study. Dent Med Probl. 2024;61(1):43–52. doi:10.17219/dmp/172243
  6. Wieckiewicz M, Martynowicz H, Lavigne G, et al. An exploratory study on the association between serotonin and sleep breathing disorders. Sci Rep. 2023;13(1):11800. doi:10.1038/s41598-023-38842-y
  7. Choi WG, Choi W, Oh TJ, et al. Inhibiting serotonin signaling through HTR2B in visceral adipose tissue improves obesity-related insulin resistance. J Clin Invest. 2021;131(23):e145331. doi:10.1172/JCI145331
  8. Yabut JM, Desjardins EM, Chan EJ, et al. Genetic deletion of mast cell serotonin synthesis prevents the development of obesity and insulin resistance. Nat Commun. 2020;11(1):463. doi:10.1038/s41467-019-14080-7
  9. Lu M, Fang F, Wang Z, Wei P, Hu C, Wei Y. Association between serum/plasma levels of adiponectin and obstructive sleep apnea hypopnea syndrome: A meta-analysis. Lipids Health Dis. 2019;18(1):30. doi:10.1186/s12944-019-0973-z
  10. Cox KH, Takahashi JS. Circadian clock genes and the transcriptional architecture of the clock mechanism. J Mol Endocrinol. 2019;63(4):R93–R102. doi:10.1530/JME-19-0153
  11. Gekakis N, Staknis D, Nguyen HB, et al. Role of the CLOCK protein in the mammalian circadian mechanism. Science. 1998;280(5369):1564–1569. doi:10.1126/science.280.5369.1564
  12. Shearman LP, Sriram S, Weaver DR, et al. Interacting molecular loops in the mammalian circadian clock. Science. 2000;288(5468):1013–1019. doi:10.1126/science.288.5468.1013
  13. Landgraf D, Wang LL, Diemer T, Welsh DK. NPAS2 compensates for loss of CLOCK in peripheral circadian oscillators. PLoS Genet. 2016;12(2):e1005882. doi:10.1371/journal.pgen.1005882
  14. Cao F, Ralph MR, Stinchcombe AR. A phenomenological mouse circadian pacemaker model. J Biol Rhythms. 2022;37(3):329–342. doi:10.1177/07487304221085455
  15. Lowrey PL, Takahashi JS. Genetics of circadian rhythms in mammalian model organisms. Adv Genet. 2011;74:175–230. doi:10.1016/B978-0-12-387690-4.00006-4
  16. Novák B, Tyson JJ. Design principles of biochemical oscillators. Nat Rev Mol Cell Biol. 2008;9(12):981–991. doi:10.1038/nrm2530
  17. Malicki M, Karuga FF, Szmyd B, Sochal M, Gabryelska A. Obstructive sleep apnea, circadian clock disruption, and metabolic consequences. Metabolites. 2022;13(1):60. doi:10.3390/metabo13010060
  18. Xu Y, Padiath QS, Shapiro RE, et al. Functional consequences of a CKIdelta mutation causing familial advanced sleep phase syndrome. Nature. 2005;434(7033):640–644. doi:10.1038/nature03453
  19. Pan X, Mota S, Zhang B. Circadian clock regulation on lipid metabolism and metabolic diseases. Adv Exp Med Biol. 2020;1276:53–66. doi:10.1007/978-981-15-6082-8_5
  20. Bass J, Takahashi JS. Circadian integration of metabolism and energetics. Science. 2010;330(6009):1349–1354. doi:10.1126/science.1195027
  21. Zhang R, Yan C, Zhou X, et al. Association of Rev-erbα in adipose tissues with type 2 diabetes mellitus amelioration after gastric bypass surgery in Goto–Kakizaki rats. Am J Physiol Regul Integr Comp Physiol. 2013;305(2):R134–R146. doi:10.1152/ajpregu.00520.2012
  22. Kooner JS, Saleheen D, Sim X, et al. Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat Genet. 2011;43(10):984–989. doi:10.1038/ng.921
  23. Yang MY, Lin PW, Lin HC, et al. Alternations of circadian clock genes expression and oscillation in obstructive sleep apnea. J Clin Med. 2019;8(10):1634. doi:10.3390/jcm8101634
  24. Canales MT, Holzworth M, Bozorgmehri S, et al. Clock gene expression is altered in veterans with sleep apnea. Physiol Genomics. 2019;51(3):77–82. doi:10.1152/physiolgenomics.00091.2018
  25. Firsov D, Bonny O. Circadian rhythms and the kidney. Nat Rev Nephrol. 2018;14(10):626–635. doi:10.1038/s41581-018-0048-9
  26. Xie T, Guo D, Luo J, et al. The relationship between HIF1α and clock gene expression in patients with obstructive sleep apnea. Nat Sci Sleep. 2022;14:381–392. doi:10.2147/NSS.S348580