Biology subjects

Fernandez-Sanles, A.

Publications and source records attributed to Fernandez-Sanles, A..

4 recordsLinked to original sources

bioRxiv2019

Identification of 20 novel loci associated to ischemic stroke. Epigenome-Wide Association Study

RationaleDNA methylation is dynamic, varies throughout the life course, and its levels are influenced by lifestyle and environmental factors, as well as by genetic variation. The leading genetic variants at stroke risk loci identified to date explain roughly 1-2% of stroke heritability. Most of these single nucleotide polymorphisms are situated within a regulatory sequence marked by DNase I hypersensitivity sites, which would indicate involvement of an epigenetic mechanism. ObjectiveTo detect epigenetic variants associated to stroke occurrence and stroke subtypes. Methods and ResultsA two-stage case-control epigenome-wide association study was designed. The discovery sample with 401 samples included 218 ischemic stroke (IS) patients, assessed at Hospital del Mar (Barcelona, Spain) and 183 controls from the REGICOR cohort. In two independent samples (N=226 and N=166), we replicated 22 CpG sites differentially methylated in IS in 21 loci, including 2 CpGs in locus ZFHX3, which includes known genetic variants associated with stroke. The pathways associated to these loci are inflammation and angiogenesis. The meta-analysis identified 384 differentially methylated CpGs, including loci of known stroke and vascular risk genetic variants, enriched by loci involved in lipid metabolism, adipogenesis, circadian clock, and glycolysis pathways. Stratification analysis by stroke subtypes revealed distinct methylation patterns. ConclusionsWe identified a set of 22 CpGs in 21 loci associated with IS. Our analysis suggests that DNA methylation changes may contribute to orchestrating gene expression that contributes to IS.

genetics↗

bioRxiv2019

DNA Methylation Biomarkers Of Myocardial Infarction And Cardiovascular Disease

ObjectiveTo assess the association between DNA methylation and acute myocardial infarction, the predictive added value of the identified methylation marks, and the causality of those associations. Approach and ResultsWe conducted a case-control, two-stage, epigenome-wide association study on acute myocardial infarction (ndiscovery=391, nvalidation=204). DNA methylation was assessed using the Infinium MethylationEPIC BeadChip (over 850,000 CpGs). DNA methylation was the exposure variable and myocardial infarction the outcome of interest. After a fixed-effects meta-analysis, 34 CpGs fulfilled Bonferroni significance. These findings were also analysed in two independent cohort studies (n[~]1,800 and n[~]2,500) with incident coronary (CHD) and cardiovascular disease (CVD). The Infinium HumanMethylation450 BeadChip was used in these two studies (over 480,000 CpGs) and only 12 of the 34 CpGs were available in those samples. Finally, we validated four of them in association with incident CHD: AHRR-mapping cg05575921, PTCD2-mapping cg25769469, intergenic cg21566642 and MPO-mapping cg04988978. The four CpGs were also associated with classical cardiovascular risk factors. A methylation risk score based on those CpGs did not improve the predictive capacity of the Framingham risk function. To assess the causal effects of those CpGs we performed Mendelian randomization analysis but only one metQTL could be identified and the results were not conclusive. ConclusionsWe have identified 34 CpGs related to acute myocardial infarction. These loci highlight the relevance of smoking, lipid metabolism, and inflammation in the biological mechanisms related to myocardial infarction. Four were additionally associated with incident CHD and CVD but did not provide additional predictive information.

genomics↗

bioRxiv2019

High-density lipoprotein characteristics and coronary heart disease: a Mendelian randomization study

BackgroundThe causal role of high-density lipoproteins (HDL) in coronary artery disease (CAD) has been questioned. Our aim was to analyze whether genetically determined quantitative and qualitative HDL characteristics were independently associated with CAD. MethodsWe designed a two-sample multivariate Mendelian randomization study with available genome-wide association summary data. We identified genetic variants associated with HDL cholesterol and apolipoprotein A-I quantity, HDL size, particle levels, and lipid content to define our genetic instrumental variables in one sample (Kettunen et al study, N=24,925) and analyzed their association with CAD risk in a different study (CARDIoGRAMplusC4D, N=184,305). We validated these results by defining our genetic variables in another database (METSIM, N=8,372) and studied their relationship with CAD in the CARDIoGRAMplusC4D dataset. To estimate the effect size of the associations of interest adjusted for other lipoprotein traits (potential pleiotropy) we used the Multi-trait-based Conditional & Joint analysis. ResultsGenetically determined HDL cholesterol and apolipoprotein A-I levels were not associated with CAD. HDL mean diameter ({beta}=0.27 [95%CI=0.19; 0.35]), cholesterol levels in very large HDLs ({beta}=0.29 [95%CI=0.17; 0.40]), and triglyceride content in very large HDLs ({beta}=0.14 [95%CI=0.040; 0.25]) were directly associated with CAD risk, whereas the cholesterol content in medium-sized HDLs ({beta}=-0.076 [95%CI=-0.10; -0.052]) was inversely related to this risk. These results were validated in the METSIM-CARDIoGRAMplusC4D data. Genetic variants linked to both HDL qualitative traits and CAD risk were located within LIPC, the APOE/C1/C4/C2 cluster, APOB, PCIF1-PLTP, and TTC39B. ConclusionsSome HDL characteristics related to size, particle distribution, and triglyceride content are related to CAD risk whilst HDL cholesterol levels are not. This relationship could be mediated by the hepatic lipase; the apolipoproteins E, C-I, and B; the phospholipid transfer protein; and the tetratricopeptide repeat domain protein 39B, which arise as potential therapeutic targets in cardiovascular disease.

epidemiology↗

bioRxiv2018

Association between long-term air pollution exposure and DNA methylation: the REGICOR study.

BackgroundLimited evidence suggests that epigenetic mechanisms may partially mediate the adverse effects of air pollution on health. Our aims were to identify new genomic loci showing differential DNA methylation associated with long-term exposure to air pollution and to replicate loci previously identified in other studies.\n\nMethodsA two-stage epigenome-wide association study was designed: 630 individuals from the REGICOR study were included in the discovery and 454 participants of the EPIC-Italy study in the validation stage. DNA methylation was assessed using the Infinium HumanMethylation450 BeadChip. NOX, NO2, PM10, PM2.5, PMcoarse, traffic intensity and traffic load exposure were measured according to the ESCAPE protocol. A systematic review was undertaken to identify those cytosine-phosphate-guanine (CpGs) associated with air pollution in previous studies and we screened for them in the discovery study.\n\nResultsIn the discovery stage of the epigenome-wide association study, 81 unique CpGs were associated with air pollution (p-value <10-5) but none of them were validated in the replication sample. Furthemore, we identified 12 CpGs in the systematic review showing differential methylation with a p-value fulfilling the Bonferroni criteria and 1642 CpGs fulfilling the false discovery rate criteria, all of which were related to PM2.5 or NO2. None of them was replicated in the discovery study, in which the top hits were located in an intergenic region on chromosome 1 (cg10893043, p-value=6.79{middle dot}10-5) and in the PXK and ARSA genes (cg16560256, p-value=2.23{middle dot}10-04; cg11953250, p-value=3.64{middle dot}10-04).\n\nConclusionsNeither new genomic loci associated with long-term air pollution were identified, nor previously identified loci were replicated. Continued efforts to test this potential association are warranted.

epidemiology↗