| Title: | HDL levels modulate the impact of type 2 diabetes susceptibility alleles in older adults |
| Journal: | Lipids in Health and Disease |
| Published: | 22 Feb 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38389069/ |
| DOI: | https://doi.org/10.1186/s12944-024-02039-7 |
| URL: | https://lipidworld.biomedcentral.com/counter/pdf/10.1186/s12944-024-02039-7 |
Publication 8670
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Abstract
BackgroundType 2 Diabetes (T2D) is influenced by genetic, environmental, and ageing factors. Ageing pathways exacerbate metabolic diseases. This study aimed to examine both clinical and genetic factors of T2D in older adults.MethodsA total of 2,909 genotyped patients were enrolled in this study. Genome Wide Association Study was conducted, comparing T2D patients to non-diabetic older adults aged ≥ 60, ≥ 65, or ≥ 70 years, respectively. Binomial logistic regressions were applied to examine the association between T2D and various risk factors. Stepwise logistic regression was conducted to explore the impact of low HDL (HDL < 40 mg/dl) on the relationship between the genetic variants and T2D. A further validation step using data from the UK Biobank with 53,779 subjects was performed.ResultsThe association of T2D with both low HDL and family history of T2D increased with the age of control groups. T2D susceptibility variants (rs7756992, rs4712523 and rs10946403) were associated with T2D, more significantly with increased age of the control group. These variants had stronger effects on T2D risk when combined with low HDL cholesterol levels, especially in older control groups.ConclusionsThe findings highlight a critical role of age, genetic predisposition, and HDL levels in T2D risk. The findings suggest that individuals over 70 years who have high HDL levels without the T2D susceptibility alleles may be at the lowest risk of developing T2D. These insights can inform tailored preventive strategies for older adults, enhancing personalized T2D risk assessments and interventions.</p>
7 Authors
- Siobhán O.' Sullivan
- Cynthia Al Hageh
- Andreas Henschel
- Stephanie Chacar
- Antoine Abchee
- Pierre Zalloua
- Moni Nader
1 Application
| Application ID | Title |
|---|---|
| 64823 | A Genomic Data Science Framework for the 1000 Arab genome project |
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