1Department of Pharmacology & Toxicology, Faculty of Medicine, American University of Beirut, Lebanon 2Department of Nutrition & Food Sciences, Faculty of Agriculture and Food Sciences, American University of Beirut, Lebanon 3Department of Internal Medicine, Faculty of Medicine, American University of Beirut Medical Center, Lebanon 4Clinical Research Institute, Faculty of Medicine, American University of Beirut Medical Center, Lebanon
In Lebanon, data stemming from national cross-sectional surveys indicated significant increasing trends in the prevalence of cardiovascular diseases and associated behavioral and age-related risk factors. To our knowledge, no data are available on relative telomere length (RTL) as a potential biomarker for age-related diseases in a Lebanese population. The aim of this study was to evaluate whether there is an association between RTL and demographic characteristics, lifestyle habits and diseases in the Lebanese. This was a cross-sectional study of 497 Lebanese subjects. Peripheral blood RTL was measured by amplifying telomere and single copy gene using real-time PCR. Mean ± SD RTL was 1.42 ± 0.83, and it was categorized into 3 tertiles. Older age (P=0.002) and wider waist circumference (WC) (P=0.001) were statistically significantly associated with shorter RTL. Multinomial logistic regression showed that subjects who had some level of sleeping difficulty had a statistically significantly shorter RTL when compared to those with no sleeping difficulties at all [OR (95% CI): 2.01 (1.11-3.62) in the first RTL tertile]. Importantly, statistically significantly shorter RTL was found with every additional 10 cm of WC [OR (95% CI): 1.30 (1.11-1.52) for first RTL tertile]. In addition, and after performing the multivariate logistic regression and adjusting for “predictors” of RTL, the odds of having hypertension or being treated for hypertension were higher in patients who had shorter RTL: OR (95% CI): 2.45 (1.36-4.44) and 2.28 (1.22-4.26) in the first RTL tertiles respectively with a similar trend, though not statistically significant, in the second RTL tertiles. This is the first study in Lebanon to show an association between age, central obesity, poor sleep and hypertension and RTL. It is hoped that telomere length measurement be potentially used as a biomarker for biological age and age-related diseases and progression in the Lebanese.
Zgheib Nathalie K,Sleiman Fatima,Nasreddine Lara, et al. Short Telomere Length is Associated with Aging, Central Obesity, Poor Sleep and Hypertension in Lebanese Individuals[J]. Aging and disease,
2018, 9(1): 77-89.
Table 1 The association of RTL with baseline characteristics and lifestyle.
Figure 1. Correlation of relative telomere length with age and waist circumference
Scatter plots showing the correlation of age (A) and waist circumference (B) with the relative telomere length of peripheral leucocyte blood respectively in males and females. The grey line and (×) represent the males (n=178) and the black line and (o) represent the females (n=319). The P-values were calculated from the linear regression analyses of the relationships between age, waist circumference and RTL in males and females, and the Pearson correlation was used.
Table 4 Stepwise multivariate logistic regression of RTL tertiles with chronic disease and laboratory values with and without adjustment with potentially significant predictors of RTL1
1.060 - 1.432
OR (95 % CI )
OR (95 % CI)
Age - 40-60 years
2.41 (1.45 - 4.02)
1.35 (0.84 - 2.19)
Age - >60 years
2.12 (1.06 - 4.23)
1.25 (0.63 - 2.48)
Education - Intermediate school
0.49 (0.27 - 0.88)
1.19 (0.68 - 2.06)
Education - Secondary school or technical diploma
0.88 (0.49 - 1.58)
1.00 (0.55 - 1.82)
Education - University degree
0.96 (0.45 - 2.06)
0.90 (0.40 - 2.01)
Any sleeping difficulty - Rarely, sometimes, or frequently
2.04 (1.13 - 3.69)
1.04 (0.58 - 1.88)
Any sleeping difficulty - Almost always
1.61 (0.90 - 2.86)
1.49 (0.87 - 2.55)
Supplementary Table 1 Stepwise multinomial logistic regression of potentially significant predictors of RTL including body mass index as a marker for obesity with RTL
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