The rest-activity rhythm, genetic susceptibility and risk of type 2 diabetes: A prospective study in UK Biobank
- PMID: 37654212
- DOI: 10.1111/dom.15236
The rest-activity rhythm, genetic susceptibility and risk of type 2 diabetes: A prospective study in UK Biobank
Abstract
Aims: This study aims to examine the association between the rest-activity rhythm (RAR) and the incidence of type 2 diabetes (T2D).
Materials and methods: In total, 97 503 participants without diabetes in the UK Biobank cohort were recruited. Wearable accelerometry was used to monitor circadian behaviour. The parameters of RAR including inter-daily stability, intra-daily variability, relative amplitude (RA), most active continuous 10 h period (M10), and least active continuous 5 h period (L5) were calculated to evaluate the robustness and regularity of the RAR. The weighted polygenic risk score for T2D (T2D-PRS) was calculated. Cox proportion hazards models were used to evaluate the survival relationship and the joint and interaction effects of RAR parameters and T2D-PRS on the occurrence of T2D.
Results: During 692 257 person-years follow-ups, a total of 2434 participants were documented. After adjustment for potential confounders, compared with participants in the highest quartile of RA and M10, the participants in the lowest quartile had a greater risk of T2D (HRRA = 2.06, 95% CI: 1.76-2.41; HRM10 = 1.33, 95% CI: 1.19-1.49). Meanwhile, the highest quartile of L5 was related to a higher risk of T2D (HR = 1.78, 95% CI: 1.55-2.24). The joint analysis showed that the high T2D-PRS with the lowest quartile of RA and M10, or highest quartile of L5 jointly increased the risk of T2D (HRRA = 4.46, 95% CI: 3.36-6.42; HRM10 = 3.15, 95% CI: 2.29-4.32; HRL5 = 3.09, 95% CI: 2.40-3.99). No modification effects of T2D-PRS on the association between the RAR parameters and risk of T2D were observed (p > .05).
Conclusion: The unbalanced RAR are associated with a greater risk of T2D, which are independent of known risk factors of T2D.
Keywords: UK Biobank; cohort; polygenic risk score; rest-activity rhythm; type 2 diabetes.
© 2023 John Wiley & Sons Ltd.
References
REFERENCES
-
- Chatterjee S, Khunti K, Davies MJ. Type 2 diabetes. Lancet. 2017;389:2239-2251. doi:10.1016/S0140-6736(17)30058-2
-
- American Diabetes Association Professional Practice Committee, Draznin B, Aroda VR, et al. 8. Obesity and weight Management for the Prevention and Treatment of type 2 diabetes: standards of medical Care in Diabetes-2022. Diabetes Care. 2022;45:S113-S124. doi:10.2337/dc22-S008
-
- Challet E, Malan A, Turek FW, Van Reeth O. Daily variations of blood glucose, acid-base state and PCO2 in rats: effect of light exposure. Neurosci Lett. 2004;355:131-135. doi:10.1016/j.neulet.2003.10.041
-
- Cailotto C, La Fleur SE, Van Heijningen C, et al. The suprachiasmatic nucleus controls the daily variation of plasma glucose via the autonomic output to the liver: are the clock genes involved? Eur J Neurosci. 2005;22:2531-2540. doi:10.1111/j.1460-9568.2005.04439.x
-
- Rakshit K, Matveyenko AV. Induction of Core circadian clock transcription factor Bmal1 enhances β-cell function and protects against obesity-induced glucose intolerance. Diabetes. 2021;70:143-154. doi:10.2337/db20-0192
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