ABCA1 gene promoter DNA methylation is associated with HDL particle profile and coronary artery disease in familial hypercholesterolemia.
ABSTRACT High-density lipoproteins cholesterol (HDL-C) level, a strong coronary artery disease (CAD) clinical biomarker, shows significant interindividual variability. However, the molecular mechanisms involved remain mostly unknown. ATP-binding cassette A1 (ABCA1) catalyzes the cholesterol transfer from peripheral cells to nascent HDL particles. Recently, a differentially methylation region was identified in ABCA1 gene promoter locus, near the first exon. Therefore, we hypothesized that DNA methylation changes at ABCA1 gene locus is one of the molecular mechanisms involved in HDL-C interindividual variability. The study was conducted in familial hypercholesterolemia (FH), a monogenic disorder associated with a high risk of CAD . Ninety-seven FH patients (all p.W66G for the LDLR gene mutation and not under lipid-lowering treatment) were recruited and finely phenotyped for DNA methylation analyses at ABCA1 gene locus. ABCA1 DNA methylation levels were found negatively correlated with circulating HDL-C (r = -0.20; p = 0.05), HDL2-phospholipid levels (r = -0.43; p = 0.04), and with a trend for association with HDL peak particle size (r = -0.38; p = 0.08). ABCA1 DNA methylation levels were also found associated with prior history of CAD (CAD = 40.2% vs. without CAD = 34.3%; p = 0.003). These results suggest that epigenetic changes within the ABCA1 gene promoter contribute to the interindividual variability in plasma HDL-C concentrations and are associated with CAD expression. These findings could change our understanding of the molecular mechanisms involved in the pathophysiological processes leading to CAD.
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ABSTRACT: Are there quantitative alterations in the proteome of normozoospermic sperm samples that are able to complete IVF but whose female partner does not achieve pregnancy? Normozoospermic sperm samples with different IVF outcomes (pregnancy versus no pregnancy) differed in the levels of at least 66 proteins. The analysis of the proteome of sperm samples with distinct fertilization capacity using low-throughput proteomic techniques resulted in the detection of a few differential proteins. Current high-throughput mass spectrometry approaches allow the identification and quantification of a substantially higher number of proteins. This was a case-control study including 31 men with normozoospermic sperm and their partners who underwent IVF with successful fertilization recruited between 2007 and 2008. Normozoospermic sperm samples from 15 men whose female partners did not achieve pregnancy after IVF (no pregnancy) and 16 men from couples that did achieve pregnancy after IVF (pregnancy) were included in this study. To perform the differential proteomic experiments, 10 no pregnancy samples and 10 pregnancy samples were separately pooled and subsequently used for tandem mass tags (TMT) protein labelling, sodium dodecyl sulphate-polyacrylamide gel electrophoresis, liquid chromatography tandem mass spectrometry (LC-MS/MS) identification and peak intensity relative protein quantification. Bioinformatic analyses were performed using UniProt Knowledgebase, DAVID and Reactome. Individual samples (n = 5 no pregnancy samples; n = 6 pregnancy samples) and aliquots from the above TMT pools were used for western blotting. By using TMT labelling and LC-MS/MS, we have detected 31 proteins present at lower abundance (ratio no pregnancy/pregnancy < 0.67) and 35 at higher abundance (ratio no pregnancy/pregnancy > 1.5) in the no pregnancy group. Bioinformatic analyses showed that the proteins with differing abundance are involved in chromatin assembly and lipoprotein metabolism (P values < 0.05). In addition, the differential abundance of one of the proteins (SRSF protein kinase 1) was further validated by western blotting using independent samples (P value < 0.01). For individual samples the amount of recovered sperm not used for IVF was low and in most of the cases insufficient for MS analysis, therefore pools of samples had to be used to this end. Alterations in the proteins involved in chromatin assembly and metabolism may result in epigenetic errors during spermatogenesis, leading to inaccurate sperm epigenetic signatures, which could ultimately prevent embryonic development. These sperm proteins may thus possibly have clinical relevance. This work was supported by the Spanish Ministry of Economy and Competitiveness (Ministerio de Economia y Competividad; FEDER BFU 2009-07118 and PI13/00699) and Fundación Salud 2000 SERONO13-015. There are no competing interests to declare.Human Reproduction 04/2014; · 4.67 Impact Factor
- Archivos de cardiología de México 03/2014;
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ABSTRACT: Gene polymorphisms associated so far with plasma lipid concentrations explain only a fraction of their heritability, which can reach up to 60%. Recent studies suggest that epigenetic modifications (DNA methylation) could contribute to explain part of this missing heritability. We therefore assessed whether the DNA methylation of key lipoprotein metabolism genes is associated with high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglyceride levels in patients with familial hypercholesterolemia (FH). Untreated FH patients (61 men and 37 women) were recruited for the measurement of blood DNA methylation levels at the ABCG1, LIPC, PLTP and SCARB1 gene loci using bisulfite pyrosequencing. ABCG1, LIPC and PLTP DNA methylation was significantly associated with HDL-C, LDL-C and triglyceride levels in a sex-specific manner (all P<0.05). FH subjects with previous history of coronary artery disease (CAD) had higher LIPC DNA methylation levels compared with FH subjects without CAD (P = 0.02). Sex-specific multivariable linear regression models showed that new and previously reported epipolymorphisms (ABCG1-CpGC3, LIPC-CpGA2, mean PLTP-CpGC, LPL-CpGA3, CETP-CpGA2, and CETP-CpGB2) significantly contribute to variations in plasma lipid levels (all P<0.001 in men and P<0.02 in women), independently of traditional predictors such as age, waist circumference, blood pressure, fasting plasma lipids and glucose levels. These results suggest that epigenetic perturbations of key lipoprotein metabolism genes are associated with plasma lipid levels, contribute to the interindividual variability and might partially explain the missing heritability of plasma lipid levels, at least in FH.Epigenetics: official journal of the DNA Methylation Society 02/2014; 9(5). · 4.58 Impact Factor