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Published on: October 23, 2020
Association of lipoprotein lipase genetic risk score with cardiometabolic risk indicators in a healthy Qatari
Maria M AlAnazi1,2, Julie A Lovegrove1,3, Karani Santhanakrishnan Vimaleswaran1,3
1Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading, United Kingdom.
Abstract:
Genetic variations within the Lipoprotein Lipase (LPL) gene have been shown to influence the risk of cardiometabolic diseases. However, their associations with cardiometabolic disease-related markers remain underexplored in Arab Qatari populations. Hence, we examined the association between a genetic risk score (GRS) based on three LPL single nucleotide polymorphisms (SNPs) and cardiometabolic indicators in a healthy Qatari population. A cross-sectional genetic association study was conducted using data from the Qatar Biobank population-based cohort, involving a sample of metabolically healthy Qatari adults (n = 6,919). The LPL-GRS was computed as the unweighted sum of risk alleles from three LPL SNPs: rs295 (C/A), rs301 (C/T), and rs320 (G/T). Associations between the GRS and metabolic markers were assessed using a generalized linear model, adjusting for age, sex, and body mass index. Individuals with high GRS (>5 risk alleles) showed a significant association with lower fat-free mass index values (β = -0.064, p = 0.029). In addition, a positive association was observed between GRS and fasting insulin levels (β = 0.035, p = 0.016). In addition, high GRS was significantly associated with lower high-density lipoprotein cholesterol (β = -0.025, p = 0.001) and higher triacylglycerol concentrations (β = 0.027, p = 0.0003) and systolic blood pressure (β = 0.007, p = 0.002), respectively. Our study shows that the LPL-GRS is associated with key cardiometabolic risk factors in this self-reported healthy Qatari population. These findings highlight the need for additional research to replicate these findings in independent and ethnically diverse cohorts, as well as the use of longitudinal studies to evaluate the predictive value of the GRS for future metabolic outcomes.
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