Artikel
Interaction of polygenetic effect allele sum scores for serum lipid levels by socioeconomic position in a population-based cohort
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Autoren
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Carina Emmel
- Institut für Medizinische Informatik, Biometrie und Epidemiologie. Universitätsklinikum Essen, Essen, Germany
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Nico Dragano
- Institut für Medizinische Soziologie, Universitätsklinikum Düsseldorf, Düsseldorf, Germany
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Mirjam Frank
- Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Essen, Germany
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Raimund Erbel
- Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Universität Duisburg-Essen, Essen, Germany
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Karl-Heinz Jöckel
- Universitätsklinikum Essen, Essen, Germany
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Börge Schmidt
- Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Essen, Germany
| Veröffentlicht: | 26. Februar 2021 |
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Gliederung
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Introduction: Serum lipid concentrations (SLC) of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL) and total cholesterol (TC) are modifiable risk factors for cardiovascular disease (CVD). Genetic research has outlined associations between various genetic loci and SLC phenotypes. Socioeconomic position (SEP) indicators also appear to be strongly related to CVD risk factors, including SLC. The aim was to investigate whether education and income as SEP indicator may interact with SLC-increasing genetic effect allele sum scores (GES) on their respective phenotype in a population-based cohort.
Methods: In the Heinz-Nixdorf Recall Study 4,518 men and women were genotyped. One lipid-increasing GES for each phenotype (HDL, LDL, TC) was calculated using information of the latest SLC genome wide meta-analysis. HDL, LDL, TC, education and income were assessed at study baseline. Age- and sex-adjusted linear regression models were fitted to investigate the association between GES and SLC, also stratified by SEP indicators as well as GESxSEP interaction terms.
Results: A 0.57 mg/dl (95%-CI: 0.48, 0.66) higher HDL level, a 1.37 mg/dl (95%-CI: 1.14, 1.60) higher LDL level and a 1.41 mg/dl (95%-CI: (1.20; 1.63) higher TC level were observed per additional effect allele of the respective GES in the whole study population. In the highest education group (≥14 years) compared to the lowest (≤10 years) stronger genetic effect size estimates per additional effect allele were present for HDL (0.58 mg/dl [95%-CI: 0.43, 0.73] vs. 0.48 mg/dl [95%-CI: 0.22, 0.75]), LDL (1.46 mg/dl [95%-CI: 1.05, 1.86] vs. 0.59 mg/dl [95%-CI: -0.11, 1.28]) and TC (1.55 mg/dl [95%-CI: 1.18, 1.92] vs. 0.84 mg/dl [95%-CI: 0.18, 1.50]). Similarly, in the highest income tercile compared to the lowest stronger genetic effect size estimates were present for HDL (0.57 mg/dl [95%-CI: 0.43, 0.73] vs. 0.55 mg/dl [95%-CI: 0.37, 0.72]) and LDL (1.31 mg/dl [95%-CI: 0.89, 1.72] vs. 1.16 mg/dl [95%-CI: 0.74, 1.58]) but not for TC (1.42 mg/dl [95%-CI: 1.05, 1.80] vs. 1.47 mg/dl [95%-CI: 1.07, 1.88]). Using the highest education group as reference, effect size estimates of interaction terms showed stronger indication of GES by low education interaction for LDL (βGESxEducation: -0.86; 95%-CI:-1.66, -0.07) compared to TC (βGESxEducation: -0.70; 95%-CI:-1.43, 0.03) and HDL (βGESxEducation: -0.11; 95%-CI: -0.41, 0.20). The effect size estimates for the GES by income interaction were directionally consistent, except for TC, but smaller in magnitude.
Conclusion: Results of the present study showed stronger genetic effects on CVD risk-decreasing HDL as well as on CVD risk-increasing LDL in groups of higher SEP, indicating the relevance of social factors for the expression of genetic health risks.
The authors declare that they have no competing interests.
The authors declare that a positive ethics committee vote has been obtained.
