Association of Sleep and Circadian Patterns and Genetic Risk with Incident Type 2 Diabetes: A Large Prospective Population-Based Cohort Study

2021 ◽  
Author(s):  
Zhi-Hao Li ◽  
Pei-Dong Zhang ◽  
Qing Chen ◽  
Xiang Gao ◽  
Vincent CH Chung ◽  
...  

Objective To examine the association of incident type 2 diabetes (T2D) risk with sleep factors, genetic risk, and their combination effects. Design Large prospective population-based cohort study. Methods This population-based prospective cohort study included 360 403 (mean [SD] age: 56.6 [8.0] years) participants without T2D at baseline from the UK Biobank. Genetic risk was categorized as high (highest quintile), intermediate (quintiles 2 to 4), and low (lowest quintile) based on a polygenic risk score for T2D. Sleep scores, including long or short sleep duration, insomnia, snoring, late chronotype, and excessive daytime sleepiness, were categorized as an unfavourable, intermediate, or favourable sleep and circadian pattern. Results During a median follow-up of 9.0 years, 13 120 incident T2D cases were recorded. Among the participants with an unfavourable sleep and circadian pattern, 6.96% (95% CI, 6.68%–7.24%) developed T2D versus 2.37% (95% CI, 2.28%–2.46%) of participants with a favourable sleep and circadian pattern (adjusted HR: 1.53, 95% CI: 1.45–1.62). Of participants with a high genetic risk, 5.53% (95% CI, 5.36%–5.69%) developed T2D versus 2.01% (95% CI, 1.91%–2.11%) of participants with a low genetic risk (adjusted HR: 2.89, 95% CI: 2.72–3.07). The association with sleep and circadian patterns was independent of genetic risk strata. Participants in the lowest quintile with an unfavourable sleep and circadian pattern were 3.97-fold more likely to develop T2D than those in the lowest quintile with a favourable sleep and circadian pattern. Conclusions Sleep and circadian patterns and genetic risk were independently associated with incident T2D. These results indicate the benefits of adhering to a healthy sleep and circadian pattern in entire populations, independent of genetic risk.

PLoS ONE ◽  
2018 ◽  
Vol 13 (5) ◽  
pp. e0195962 ◽  
Author(s):  
Christopher A. Tait ◽  
Mary R. L’Abbé ◽  
Peter M. Smith ◽  
Laura C. Rosella

2008 ◽  
Vol 158 (5) ◽  
pp. R1-R5 ◽  
Author(s):  
Christian Herder ◽  
Thomas Illig ◽  
Jens Baumert ◽  
Martina Müller ◽  
Norman Klopp ◽  
...  

ObjectiveRegulated on activation, normal T-cell expressed and secreted (RANTES)/chemokine(C-C motif) ligand (CCL5) is expressed by adipocytes, and serum levels of RANTES are increased in obesity and type 2 diabetes. The aim of this study was to test the hypothesis that RANTES is involved in the pathogenesis of type 2 diabetes by analyzing the triangular association between CCL5 gene polymorphisms, systemic RANTES concentrations, and incident type 2 diabetes in a large prospective study.Subjects and methodsThe study is based on 502 individuals (293 men and 209 women) and 1632 individuals (859 men and 773 women) with and without incident type 2 diabetes from the population-based MONItoring of Trends and Determinants in Cardiovascular Disease (MONICA)/Cooperative Health Research in the Region of Augsburg (KORA) case–cohort study respectively (mean follow-up time±s.d. 10.1±4.9 years). CCL5 genotypes and RANTES serum concentrations were determined and associations between genotypes, haplotypes, serum levels, and incident type 2 diabetes were assessed.ResultsMinor alleles of four single nucleotide polymorphisms were associated with lower RANTES levels (Padditive between 1.2×10−9 and 3.1×10−8), but neither genotypes, haplotypes, nor serum levels were associated with incident type 2 diabetes.ConclusionsOur data suggest that RANTES/CCL5 gene variants and serum levels are not causally related with type 2 diabetes and that elevated RANTES levels in patients with type 2 diabetes may be a consequence of hyperglycemia. However, our findings cannot preclude a local role in adipose tissue where RANTES expression may contribute to leukocyte infiltration and a proinflammatory state.


2014 ◽  
Vol 26 (2) ◽  
pp. 827-833 ◽  
Author(s):  
D. Martinez-Laguna ◽  
C. Tebe ◽  
M. K. Javaid ◽  
X. Nogues ◽  
N. K. Arden ◽  
...  

Metabolism ◽  
2016 ◽  
Vol 65 (6) ◽  
pp. 883-892 ◽  
Author(s):  
Joule J. Li ◽  
Gary A. Wittert ◽  
Andrew Vincent ◽  
Evan Atlantis ◽  
Zumin Shi ◽  
...  

2017 ◽  
Vol 64 (11) ◽  
pp. 1105-1114 ◽  
Author(s):  
Kazuteru Mitsuhashi ◽  
Yoshitaka Hashimoto ◽  
Masahide Hamaguchi ◽  
Akihiro Obora ◽  
Takao Kojima ◽  
...  

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