Decrease of Lp(a) during weight reduction in obese children is modified by the apo(a) kringle-IV copy number variation

Brandstätter, Anita; Lingenhel, Arno; Zwiauer, Karl; Strobl, Wolfgang; Kronenberg, Florian

doi:10.1038/ijo.2009.144

Cited by 15 publications

(11 citation statements)

References 40 publications

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“…Finally, Brandstatter el al. 32 observed that after a 3-week hypocaloric diet in children, a 6.6% decrease in body weight leads to ~ 20% decrease in Lp(a) levels, which is comparable to the decline seen in LDL-C and triglycerides. These findings suggest that BMI is strongly related to Lp(a) and that ethnicity may affect this relationship.…”

Section: Discussionmentioning

confidence: 71%

Prevalence and status of Lipoprotein (a) among Lebanese school children

Gannagé‐Yared

Lahoud

Younes

et al. 2020

Sci Rep

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Lipoprotein a (Lp(a) is an independent risk factor for atherosclerotic cardiovascular disease. The prevalence of high Lipoprotein (a) (Lp(a)) in the Lebanese pediatric population is unknown. Our study aims to assess this prevalence and to study the relationship of Lp(a) with the lipid profile, age, body mass index (BMI) and socio-economic status (SES) in Lebanese schoolchildren. A total of 961 children aged 8–18 years (497 boys and 464 girls) were recruited from ten private and public schools in 2013–2014 using a stratified random sample. Schools were selected from the Greater Beirut and Mount Lebanon areas, and were categorized into three subgroups according to the schools’ SES status (high, medium, low). Lp(a) was assayed in 2018 on samples previously frozen at − 80 °C. Abnormal Lp(a) levels (≥ 75 nmol/L) were observed in 14.4% of the overall sample (13.5% for boys,15.3% of girls p = 0.56). The median of Lp(a) was 20(10–50) in the whole sample with no significant gender difference. No significant relationship was found between Lp(a) and age. However, Lp(a) was significantly correlated with BMI in whole sample, as well as in boys and girls (p = 0.02, p = 0.03, p = 0.03, respectively). A significant correlation was found between Lp(a) and non-HDL-C in the whole sample as well as in boys and girls (respectively p < 0.001,p = 0.024 and p = 0.03), but not with triglycerides and HDL-C. In a multivariate linear regression analysis, Lp(a) was only independently associated with BMI and non-HDL-C in boys and girls. Lp(a) was independently associated with BMI and non-HDL-C while no significant relationship was observed with age and sex confirming the strong genetic determination of Lp(a).

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Section: Discussionmentioning

confidence: 71%

Prevalence and status of Lipoprotein (a) among Lebanese school children

Gannagé‐Yared

Lahoud

Younes

et al. 2020

Sci Rep

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“…Known obesogenic factors such as physical activity and food intake have been shown to account for a significant portion of the variance in BMI with estimates ranging 5–10% (Chambers and Swanson 2010; Newby et al 2006; French et al 1994; Jebb and Moore 1999). Additionally, research is beginning to elucidate G×E affecting BMI (Rampersaud et al 2008; Lappalainen et al 2009; Qi et al 2008; Brandsttter et al 2009; Razquin et al 2010). At least two genes included in the current GRSS show evidence for G×E effects.…”

Section: Discussionmentioning

confidence: 99%

Genetic risk sum score comprised of common polygenic variation is associated with body mass index

et al. 2010

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Genome-wide association studies (GWAS) of body mass index (BMI) using large samples have yielded approximately a dozen robustly associated variants and implicated additional loci. Individually these variants have small effects and in aggregate explain a small proportion of the variance. As a result, replication attempts have limited power to achieve genome-wide significance, even with several thousand subjects. Since there is strong prior evidence for genetic influence on BMI for specific variants, alternative approaches to replication can be applied. Instead of testing individual loci sequentially, a genetic risk sum score (GRSS) summarizing the total number of risk alleles can be tested. In the current study, GRSS comprising 56 top variants catalogued from two large meta-analyses was tested for association with BMI in the Molecular Genetics of Schizophrenia controls (2,653 European-Americans, 973 African-Americans). After accounting for covariates known to influence BMI (ancestry, sex, age), GRSS was highly associated with BMI (p value = 3.19E−06) although explained a limited amount of the variance (0.66%). However, area under receiver operator criteria curve (AUC) estimates indicated that the GRSS and covariates significantly predicted overweight and obesity classification with maximum discriminative ability for predicting class III obesity (AUC = 0.697). The relative contributions of the individual loci to GRSS were examined post hoc and the results were not due to a few highly significant variants, but rather the result of numerous variants of small effect. This study provides evidence of the utility of a GRSS as an alternative approach to replication of common polygenic variation in complex traits.

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“…Rare variants could have considerable effects in singular individuals. Another, yet unexplored possibility is the influence of CNVs, which are involved in the genetic predisposition to common diseases or quantitative phenotypes [14]. GIANT found that the SNP most strongly associated with BMI was linked to a 45-kb deletion polymorphism [15].…”

Section: Discussionmentioning

confidence: 99%

Sex and age interaction with genetic association of atherogenic uric acid concentrations

et al. 2010

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Background High serum uric acid levels are associated with gout, atherosclerosis and cardiovascular disease. Three genes (SLC2A9, ABCG2, and SLC17A3) were reported to be involved in the regulation of uric acid levels. Research Design and Methods: SNPs rs2231142 (ABCG2) and rs1165205 (SLC17A3) were genotyped in three cohorts (n = 4492) and combined with previously genotyped SNPs within SLC2A9 (rs6855911, rs7442295, rs6449213, rs12510549). Results Each copy of the minor allele decreased uric acid levels by 0.30–0.38 mg/dL for SLC2A9 (p values: 10−20–10−36) and increased levels by 0.34 mg/dL for ABCG2 (p = 1.1×10−16). SLC17A3 influenced uric acid levels only modestly. Together the SNPs showed graded associations with uric acid levels of 0.111 mg/dL per risk allele (p = 3.8×10−42). In addition, we observed a sex-specific interaction of age with the association of SLC2A9 SNPs with uric acid levels, where increasing age strengthened the association of SNPs in women and decreased the association in men. Conclusions Genetic variants within SLC2A9, ABCG2 and SLC17A3 show highly significant associations with uric acid levels, and for SNPs within SLC2A9 this association is strongly modified by age and sex.

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Decrease of Lp(a) during weight reduction in obese children is modified by the apo(a) kringle-IV copy number variation

Cited by 15 publications

References 40 publications

Prevalence and status of Lipoprotein (a) among Lebanese school children

Prevalence and status of Lipoprotein (a) among Lebanese school children

Genetic risk sum score comprised of common polygenic variation is associated with body mass index

Sex and age interaction with genetic association of atherogenic uric acid concentrations

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